Presentations -
-
Advanced Multimodal Analysis of Black Cattle Mounting Behavior Using YOLO and Open-World Object Detection Techniques International conference
Su Myat Noe, Thi Thi Zin, Pyke Tin, and I. Kobayashi
2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24) 2025.3.2
Event date： 2025.2.27 - 2025.3.2
Language：English Presentation type：Oral presentation (general)
-
A Markovian Queueing Model for Internet of Things International conference
Pyke Tin, Thi Thi Zin, H. Hama
2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24) 2025.3.2
Event date： 2025.2.27 - 2025.3.2
Language：English Presentation type：Oral presentation (general)
-
Vision-Based Person Re-Identification Through Gait Recognition Using Long Short-Term Memory International conference
Cho Nilar Phyo, R. Tanno, Thi Thi Zin, Pyke Tin
2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24) 2025.3.2
Event date： 2025.2.27 - 2025.3.2
Language：English Presentation type：Oral presentation (general)
-
Quantifying Elderly Walking States Using Keypoint Data from OpenPose and Image Processing International conference
R. Tanno, Cho Nilar Phyo and Thi Thi Zin
2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24) 2025.3.2
Event date： 2025.2.27 - 2025.3.2
Language：English Presentation type：Oral presentation (general)
-
Quantitative assessment of fetal heart rate variability using Mahalanobis distance for pH classification
2024.12.21
Event date： 2024.12.21 - 2024.12.22
Language：English Presentation type：Oral presentation (general)
-
軽量なPointNet++モデルを用いたカラー点群に基づく牛識別システム
Pyae Phyo Kyaw, Thi Thi Zin, Pyke Tin, 相川 勝, 小林 郁雄
第26回日本知能情報ファジィ学会九州支部学術講演会 2024.12.21
Event date： 2024.12.21 - 2024.12.22
Language：English Presentation type：Oral presentation (general)
-
深度カメラを用いた高齢者の行動推定に関する研究
中嶋麗文，Thi Thi Zin，近藤 千尋，渡邉 信二
第37回バイオメディカル・ファジィ・システム学会年次大会 (BMFSA2024) 2024.12.14
Event date： 2024.12.14 - 2024.12.15
Language：Japanese Presentation type：Oral presentation (general)
-
Analyzing Parameter Patterns in YOLOv5-based Elderly Person Detection Across Variations of Data International conference
Ye Htet, Thi Thi Zin, Pyke Tin, H. Tamura, K. Kondo, S. Watanabe, E. Chosa
2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS) 2024.9.25
Event date： 2024.9.23 - 2024.9.25
Language：English Presentation type：Oral presentation (general)
-
Fusion of Strategic Queueing Theory and AI for Smart City Telecommunication System International conference
Thi Thi Zin, Aung Si Thu Moe, Cho Nilar Phyo, Pyke Tin
2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS) 2024.9.25
Event date： 2024.9.23 - 2024.9.25
Language：English Presentation type：Oral presentation (general)
-
Comparative Study of Predicting Fetal pH Level based on Heart Rate Variability International conference
Cho Nilar Phyo, Tunn Cho Lwin, Pyae Phyo Kyaw, E. Kino, T. Ikenoue, Pyke Tin and Thi Thi Zin
The 18th International Conference on Innovative Computing, Information and Control (ICICIC2024) 2024.9.12
Event date： 2024.9.10 - 2024.9.13
Language：English Presentation type：Oral presentation (general)
-
Integrating Entropy Measures of Fetal Heart Rate Variability with Digital Twin Technology to Enhance Fetal Monitoring International conference
Tunn Cho Lwin, Thi Thi Zin, Pyae Phyo Kyaw, Pyke Tin, E. Kino and T. Ikenoue
The 18th International Conference on Innovative Computing, Information and Control (ICICIC2024) 2024.9.12
Event date： 2024.9.10 - 2024.9.13
Language：English Presentation type：Oral presentation (general)
-
A Study on the Analysis and Classification of Gait Status Using Gait Information International conference
R. Tanno, Thi Thi Zin and Cho Nilar Phyo
The 18th International Conference on Innovative Computing, Information and Control (ICICIC2024) 2024.9.12
Event date： 2024.9.10 - 2024.9.13
Language：English Presentation type：Oral presentation (general)
-
Utilizing Behavioral Features for Predicting Calving Time International conference
Wai Hnin Eandrar Mg, Pyke Tin, M. Aikawa, I. Kobayashi, Y. Horii, K. Honkawa, Thi Thi Zin
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Research on Individual Identification of Walking Cows using a 3D Camera International conference
Y. Shiihara, Thi Thi Zin, M. Aikawa and I. Kobayashi
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
A Study on Health Management by Behavior Analysis of Calve International conference
T. Nishiyama, K. Shiiya, M. Aikawa, I. Kobayashi, Thi Thi Zin
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Applying Digital Restoration Techniques in Preservation of Ancient Murals using Diffusion Based Inpainting International coauthorship International conference
Khant Khant Win Tint, Mie Mie Tin, Thi Thi Zin and Pyke Tin
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Cow’s Back Surface Segmentation of Point-cloud Image using PointNet++ for Individual Identification International conference
Pyae Phyo Kyaw, Pyke Tin, Masaru Aikawa, Ikuo Kobayashi, Thi Thi Zin
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Cattle Lameness Classification Using Cattle Back Depth Information International conference
San Chain Tun, Pyke Tin, M. Aikawa, I. Kobayashi and Thi Thi Zin
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Automatic Body Temperature Detection in Calves and Alarm System Using Thermographic Camera International conference
Aung Si Thu Moe, Thi Thi Zin, M. Aikawa and I. Kobayashi
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Identification of Rumination Patterns in Cattle Through Optical Flow Analysis and Machine Learning Techniques International conference
T. Ishikawa, Thi Thi Zin, M. Aikawa, I. Kobayashi
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
From Vision to Vocabulary: A Multimodal Approach to Detect and Track Black Cattle Behaviors International conference
Su Myat Noe, Thi Thi Zin, Pyke Tin and I. Kobayashi
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Cattle Lameness Detection Using Leg Region Keypoints from a Single RGB Camera International conference
Bo Bo Myint, Thi Thi Zin, M. Aikawa, I. Kobayashi and Pyke Tin
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Automated Cattle Identification via Image-Based Ear Tag Recognition International conference
Y. Shimizu, Thi Thi Zin, M. Aikawa and I. Kobayashi
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Evaluation of Body Condition Score for walking dairy cows using 3D camera International conference
M. Chikunami, Thi Thi Zin, M. Aikawa, I. Kobayashi
The 16th International Conference On Genetic and Evolutionary Computing (ICGEC-2024) 2024.8.28
Event date： 2024.8.28 - 2024.8.29
Language：English Presentation type：Oral presentation (general)
-
Internet of Things (IoT) in Aquaculture: Revolutionizing the Blue Economy Invited International conference
Thi Thi Zin
The 3rd National and 1 st International Conference on Agricultural Innovation and Natural Resources 2024.8.15
Event date： 2024.8.15 - 2024.8.17
Language：English Presentation type：Oral presentation (general)
-
Enhancing Fetal Heart Rate Monitoring Through Digital Twin Technology International conference
Tunn Cho Lwin, Thi Thi Zin, Pyke Tin, T. Ikenoue, E. Kino
2024 IEEE Gaming, Entertainment, and Media Conference (GEM) 2024.6.6
Event date： 2024.6.5 - 2024.6.7
Language：English Presentation type：Poster presentation
-
A Stochastics Branching Process Model for Analyzing Rumor Spreading in Social Media Networks International conference
Thi Thi Zin, Pyke Tin, H. Hama
2024 IEEE Gaming, Entertainment, and Media Conference (GEM) 2024.6.7
Event date： 2024.6.5 - 2024.6.7
Language：English Presentation type：Oral presentation (general)
-
A Markovian Game Theoretic Framework for Analysing a Queueing System with Multiple Servers International conference
Pyke Tin, Thi Thi Zin
2024 IEEE Gaming, Entertainment, and Media Conference (GEM) 2024.6.7
Event date： 2024.6.5 - 2024.6.7
Language：English Presentation type：Oral presentation (general)
-
Automatic Cattle Detection and Tracking for Lameness Classification Using a Single Side-View Camera International conference
Bo Bo Myint, T. Onizuka, Pyke Tin, M. Aikawa, I. Kobayashi, Thi Thi Zin
Second International Symposium on Data-Driven Intelligent Optimization for Decision Making (DIODM2024) 2024.3.26
Event date： 2024.3.24 - 2024.3.27
Language：English Presentation type：Oral presentation (general)
-
画像処理技術を用いた歩行状態の数値化に関する研究
丹野 龍晟、ティティズイン
動的画像処理実利用化 ワークショップ2024 (DIA 2024) 2024.3.4
Event date： 2024.3.4 - 2024.3.5
Language：Japanese Presentation type：Poster presentation
-
Kalman Velocity-based Multi-Stage Classification Approach for Recognizing Black Cow Actions International conference
Cho Cho Aye, Thi Thi Zin, M. Aikawa, I. Kobayashi
2024 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24) 2024.2.29
Event date： 2024.2.27 - 2024.3.1
Language：English Presentation type：Oral presentation (general)
-
A Novel Stochastic Model for Analysing Heart Rate Variability in the Heart-Brain Signal Communication System International conference
Thi Thi Zin, Tunn Cho Lwin, Pyke Tin
2024 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24) 2024.2.29
Event date： 2024.2.27 - 2024.3.1
Language：English Presentation type：Oral presentation (general)
-
Enhancing Precision Agriculture: Innovative Tracking Solutions for Black Cattle Monitoring International conference
Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi
2024 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24) 2024.2.29
Event date： 2024.2.27 - 2024.3.1
Language：English Presentation type：Oral presentation (general)
-
Transition-Aware Elderly Action Recognition: Unveiling Insights with CNN-RNN Integration, International conference
Ye Htet, Thi Thi Zin, H. Tamura, K. Kondo, E. Chosa
2024 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24) 2024.2.29
Event date： 2024.2.27 - 2024.3.1
Language：English Presentation type：Oral presentation (general)
-
ディープラーニングを用いた視覚ベースの侵入者検知システムに関する研究
Cho Nilar Phyo, Thi Thi Zin and Pyke Tin
画像電子学会 第307回研究会 2024.2.26
Event date： 2024.2.26 - 2024.2.27
Language：Japanese Presentation type：Oral presentation (general)
-
Human Behavior Recognition Based on Angle and Distance Features Using SVM
2024.2.23
Event date： 2024.2.22 - 2024.2.23
Language：Japanese Presentation type：Oral presentation (general)
-
An Innovative Framework for Cattle Activity Monitoring: Combining AI-Based Markov Chain Model with IoT Devices International conference
Y. Hashimoto, Thi Thi Zin, Pyke Tin, I. Kobayashi and H. Hama
The 9rd International Conference on Science and Technology (ICST UGM 2023), 2023.11.1
Event date： 2023.11.1 - 2023.11.2
Language：English Presentation type：Oral presentation (general)
-
Evaluating Imputation Strategies for Handling Missing Data: A Comparative Study International conference
Tunn Cho Lwin, Pyke Tin and Thi Thi Zin
2023 IEEE 12th Global Conference on Consumer Electronics (GCCE2023) 2023.10.11
Event date： 2023.10.10 - 2023.10.13
Language：English Presentation type：Oral presentation (general)
-
A Study on Assessment of Falling Risk in the Elderly Using a Balance Task International conference
K. Kamahori, Thi Thi Zin
2023 IEEE 12th Global Conference on Consumer Electronics (GCCE2023) 2023.10.11
Event date： 2023.10.10 - 2023.10.13
Language：English Presentation type：Oral presentation (general)
-
Paper Title: Digital Transformation (DX) Solution for Monitoring Mycoplasma Infectious Disease in Calves: A Worldwide Health Challenge International conference
Cho Nilar Phyo, Pyke Tin, Hiromitsu Hama, Thi Thi Zin
International Conference on Genetic and Evolutionary Computing (ICGEC-2023) 2023.10.7
Event date： 2023.10.6 - 2023.10.8
Language：English Presentation type：Oral presentation (general)
-
AI Driven Movement Rate Variability Analysis Around the Time of Calving Events in Cattle International conference
Wai Hnin Eaindrar Mg, Pyke Tin, Aikawa, M., Kobayashi, I., Horii, Y., Honkawa, K. and Thi Thi Zin
International Conference on Genetic and Evolutionary Computing (ICGEC-2023) 2023.10.7
Event date： 2023.10.6 - 2023.10.8
Language：English Presentation type：Oral presentation (general)
-
Temporal-dependent Features Based Inter-Action Transition State Recognition for Eldercare System International conference
Ye Htet, Thi Thi Zin, H. Tamura, K. Kondo, E. Chosa
2023 IEEE 13th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) 2023.9.4
Event date： 2023.9.2 - 2023.9.5
Language：English Presentation type：Oral presentation (general)
-
Markov Chain Modelling for Heart Rate Variability Analysis: Bridging Artificial Intelligence and Physiological Data International conference
Thi Thi Zin, Pyke Tin
2023 IEEE 13th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) 2023.9.4
Event date： 2023.9.2 - 2023.9.5
Language：English Presentation type：Oral presentation (general)
-
Efficient Segment-Anything Model for Automatic Mask Region Extraction in Livestock Monitoring International conference
Su Myat Noe, Thi Thi Zin, Pyke Tin and I. Kobyashi
2023 IEEE 13th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) 2023.9.4
Event date： 2023.9.2 - 2023.9.5
Language：English Presentation type：Oral presentation (general)
-
Ancient Murals Restoration using Diffusion-based Methods International coauthorship International conference
Khant Khant Win Tint, Mie Mie Tin, Thi Thi Zin, Pyke Tin
The 17th International Conference on Innovative Computing, Information and Control (ICICIC2023) 2023.8.30
Event date： 2023.8.29 - 2023.8.31
Language：English Presentation type：Oral presentation (general)
-
Worker Detection and Tracking System for Data Indicator Analysis to Improve Work Efficiency in a Factory International conference
I. Hidaka, S. Inoue, T. Ishikawa, H. Tamura, Thi Thi Zin
The 17th International Conference on Innovative Computing, Information and Control (ICICIC2023) 2023.8.30
Event date： 2023.8.29 - 2023.8.31
Language：English Presentation type：Oral presentation (general)
-
A Study on Early Detection of Otitis Media in Calves using RGB and Thermographic Cameras International conference
T. Nishiyama, K. Shiiya, M. Aikawa, I. Kobayashi, Thi Thi Zin
The 17th International Conference on Innovative Computing, Information and Control (ICICIC2023) 2023.8.30
Event date： 2023.8.29 - 2023.8.31
Language：English Presentation type：Oral presentation (general)
-
Evaluation of BCS for walking dairy cows using 3D camera International conference
M. Chikunami, Thi Thi Zin, M. Aikawa, I. Kobayashi
The 17th International Conference on Innovative Computing, Information and Control (ICICIC2023) 2023.8.30
Event date： 2023.8.29 - 2023.8.31
Language：English Presentation type：Oral presentation (general)
-
Interdisciplinary Approach to Smart Farming Invited International conference
Thi Thi Zin
The 2nd Conference on Agricultural Innovation and Natural Resources 2023 2023.8.18
Event date： 2023.8.17 - 2023.8.18
Language：English Presentation type：Oral presentation (general)
-
Cattle Lameness Detection System in Modern Dairy Farm Using Cutting-Edge Methods Invited International conference
Thi Thi Zin
The Second Sakura Workshop for Consumer Electronics, Computer, Communication, and Information Technologies (Taichaung) 2023.3.27
Event date： 2023.3.27 - 2023.3.29
Language：English Presentation type：Symposium, workshop panel (public)
Venue：Taichaung Country：Taiwan, Province of China
-
A Study of Real-Time Action Recognition for the Elderly with Stereo Depth Camera International conference
Y Htet and Thi Thi Zin
The Second Sakura Workshop for Consumer Electronics, Computer, Communication, and Information Technologies (Taichaung) 2023.3.27
Event date： 2023.3.27 - 2023.3.29
Language：English Presentation type：Symposium, workshop panel (public)
Venue：Taichaung Country：Taiwan, Province of China
-
A Study on Automatic Black Cattle Tracking with Computer Vision and Deep Learning International conference
Su Myat Noe and Thi Thi Zin
The Second Sakura Workshop for Consumer Electronics, Computer, Communication, and Information Technologies (Taichaung) 2023.3.27
Event date： 2023.3.27 - 2023.3.29
Language：English Presentation type：Symposium, workshop panel (public)
Venue：Taichaung Country：Taiwan, Province of China
-
Assessing Dairy Cow Lameness using Principal Component Analysis on 3D Images Invited International conference
Pyke Tin and Thi Thi Zin
The Second Sakura Workshop for Consumer Electronics, Computer, Communication, and Information Technologies (Taichaung) 2023.3.27
Event date： 2023.3.27 - 2023.3.29
Language：English Presentation type：Symposium, workshop panel (public)
Venue：Taichaung Country：Taiwan, Province of China
-
A Study on the Possibility of Distinguishing between Parkinson's disease and Essential Tremor using Motor Symptoms Observed by an RGB camera
The 35th Annual Conference of Biomedical Fuzzy Systems Association (BMFSA2022) 2022.12.17
Event date： 2022.12.17 - 2022.12.18
Language：Japanese Presentation type：Oral presentation (general)
Movements that appear unconsciously are called involuntary movements. Especially, rhythmic involuntary movements are called tremors. Tremor interferes with daily life and is one of the characteristic symptoms of neurological disorders such as Parkinson's disease (PD) and essential tremor (ET). Symptoms and progression of PD patients are assessed by a neurologist through neurological examination and interview according to the revised Unified Parkinson's Disease Rating Scale (UPDRS) sponsored by the Movement Disorders Society (MDS). PD is associated with other symptoms such as bradykinesia, whereas ET is characterized by tremor alone. However, in the early onset of PD, other symptoms may not be noticeable, and even neurologists may find it difficult to differentiate it from ET. In this paper, to solve this issue of getting lost in this judgment, consider whether it is possible to distinguish between PD and ET two types of neurological disorders from two approaches, time domain and frequency domain which from observed tremor movement by using an RGB camera.
-
Tracking A Group of Black Cows Using SORT based Tracking Algorithm
Cho Cho Aye, Thi Thi Zin, M. Aikawa, I. Kobayashi
バイオメディカル・ファジィ・システム学会 第 35 回年次大会 2022.12.17
Event date： 2022.12.17 - 2022.12.18
Language：English Presentation type：Oral presentation (general)
-
Artificial Intelligence Topping on Spectral Analysis or Lameness Detection in Dairy Cattle
Thi Thi Zin, Ye Htet, San Chain Tun and Pyke Tin
バイオメディカル・ファジィ・システム学会 第 35 回年次大会 2022.12.17
Event date： 2022.12.17 - 2022.12.18
Language：English Presentation type：Oral presentation (general)
-
Cattle Lameness Detection using Advanced Digitization Technologies Invited International conference
Thi Thi Zin, T. Onizuka, San Chain Tun, Su Larb Mon, Pyke Tin, I. Kobayashi
第4回韓国‐日本合同シンポジウム (Miyazaki, Japan) 2022.10.31 宮崎大学CADIC
Event date： 2022.10.31
Language：English Presentation type：Symposium, workshop panel (nominated)
Venue：Miyazaki, Japan Country：Japan
-
Cow Lameness Detection Using Depth Image Analysis International conference
San Chain Tun, Thi Thi Zin, Pyke Tin, I. Kobayashi
2022 IEEE 11th Global Conference on Consumer Electronics (GCCE) (Osaka, Japan) 2022.10.19 IEEE Consumer Technology Society
Event date： 2022.10.18 - 2022.10.21
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
In this paper, we introduce to detect cow lameness by using a depth video camera from the top view position. To classify cow lameness, we first extract the sequences of depth value of the cow body region and the maximum value of the back cow area. Then, we will find the average from the maximum height values of the cow backbone area. By using the average values as a feature vector, we classify the cow lameness with the aid of the Support Vector Machine (SVM). To confirm, we perform some experiments by using depth camera images on a real-life dairy farm. The experimental result shows that our proposed method is promising.
-
Video-based Automatic Cattle Identification System International conference
Su Larb Mon, Thi Thi Zin, Pyke Tin, I. Kobayashi
2022 IEEE 11th Global Conference on Consumer Electronics (GCCE) (Osaka, Japan) 2022.10.19 IEEE Consumer Technology Society
Event date： 2022.10.18 - 2022.10.21
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
In this paper, we propose a method to identify the cattle by using video sequences. In order to do so, we first collect 360-degree top-view video sequences to form dataset. The proposed system is composed of two parts: cattle detection and cattle identification. In the detection process, we utilize YOLOv5(Y ou Only Look Once) model to detect the cattle region in the lane. In this stage, cattle’s location and region information are extracted and the cropped images of detected cattle regions are saved for the next stage. We then apply Convolutional Neural Network model (VGG16) to extract the features which will be used to identify individual cattle. For the classification, the proposed system used two supervised machine learning methods, Random Forest and SVM (Support Vector Machine). The accuracy of Random Forest is 98.5% and the accuracy of SVM is 99.6%. After comparing the accuracy rate of two methods, SVM get the better accuracy result. The proposed system achieved the accuracy of over 90% for both cattle detection and identification.
-
Cattle Pose Classification System Using DeepLabCut and SVM Model International conference
May Phyu Khin, Thi Thi Zin, Cho Cho Mar, Pyke Tin, Y. Horii
2022 IEEE 11th Global Conference on Consumer Electronics (GCCE) (Osaka, Japan) 2022.10.19 IEEE Consumer Technology Society
Event date： 2022.10.18 - 2022.10.21
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
This paper proposes the cattle pose classification system by using video-based tracking result. The proposed system is composed of two processes namely feature extraction and classification. In the feature extraction, we employ DeepLabCut network to obtain location feature points which are to be combined with cattle bounding box region values. For classification process, the SVM (Support Vector Machine) classifier will be used. To confirm the proposed method, we tested some experimental results by using the video sequences taken in some real-life dairy farms and classify six poses such as “standing”, “sitting”, “eating”, “drinking”, “sitting with leg extend” and “tail raised”. We got average 88.75% accuracy for all poses.
-
Hybrid Approach: Markov Monte Carlo and Naïve Bayes Theorem to Predict Dairy Cow Calving Time International conference
Thi Thi Zin, Swe Zar Maw, Pyke Tin, Y. Horii and H. Hama
16th International Conference on Innovative Computing, Information and Control (ICICIC2022) (Online) 2022.9.15 ICIC International
Event date： 2022.9.15 - 2022.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
In this paper, we propose a hybrid approach combing Markov Monte Carlo simulation and the Bayesian method to predict the time to the occurrence of calving events in dairy cows. A total of 30 individual dairy cows were monitored continuously under 24-hour video surveillance prior to calving. The video was annotated for the behaviors of lying, the transition from lying to standing, standing, and the transition from standing to lying for each cow from 72 hours and 168 hours prior to calving. We then derive the corresponding probabilities for each behavior. By using these probabilities, the Markov Monte Carlo simulations are performed to generate the behavior patterns of each cow prior to calving. We then investigate three types of datasets: actual, simulated, and a mixture of the two by using a Naïve Bayes Classifier to perform the prediction process. The experimental results showed that the hybrid approach correctly classified the calving event cent by cent.
-
Cattle Lameness Detection by Using Image Processing Technology International conference
T. Onizuka, Thi Thi Zin, I. Kobayashi
16th International Conference on Innovative Computing, Information and Control (ICICIC2022) (Online) 2022.9.15 ICIC International
Event date： 2022.9.15 - 2022.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
Lameness is one of the three major diseases of dairy cows, mastitis, reproductive disorders, and limb and hoof diseases. Symptoms of lameness include pain and discomfort in the legs when walking, limping legs, and abnormal movements such as rounding of the back. Among the three major diseases, limb and hoof diseases in dairy cattle are needed to be detected in times, otherwise as the symptoms worsen, diseases such as mastitis and reproductive disorders may occur, leading to a decrease in productivity. Therefore, it is important to detect and treat cows with symptoms of lameness as early as possible. In this paper, we propose a method for cattle lameness detection using an RGB camera and analysing the walking behaviour of cows. Our proposed method can classify cows as healthy or lame with high accuracy. Moreover, we have performed a series of real-life experiments to confirm the effectiveness of the classification results comparing with lameness diagnosis by experts.
-
Comparative Study on Color Spaces, Distance Measures and Pretrained Deep Neural Networks for Cow Recognition International conference
Cho Cho Mar, Thi Thi Zin, Pyke Tin, I. Kobayashi, Y. Horii and K. Honkawa5
16th International Conference on Innovative Computing, Information and Control (ICICIC2022) (Online) 2022.9.15 ICIC International
Event date： 2022.9.15 - 2022.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
As the cattle monitoring system plays as a crucial role in livestock production and dairy farming to cover the deficiencies in labor for continuous monitoring for each cattle. Robust object detection and tracking system boosts the performance and reliability of autonomous monitoring systems. The recognition task is also important to build the powerful tracking system. The main objective of this paper is to perform the recognition task by analyzing and comparing different color spaces and distance measures to choose the optimal ones. We extracted color moment features and co-occurrence matrix (CM) features from various color spaces: RGB, YCbCr, XYZ, HSV, CIElab, and gray level. We compare those features using different distance measures based on the accuracy values. We also make experiments on different Deep Learning pretrained networks to extract CNN (Convolutional Neural Network) features, and we compared the accuracy values on the classification results with Support Vector Machine (SVM) method. These experiments are tested on the cow dataset that are created from the 2 hours continuous video.
-
A Conceptual Framework and Operational Simulation Model for Cattle Lameness Detection International conference
Thi Thi Zin, Pyke Tin
16th International Conference on Innovative Computing, Information and Control (ICICIC2022) (Online) 2022.9.15 ICIC International
Event date： 2022.9.15 - 2022.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
In this paper, we introduce a conceptual framework and operational simulation model for cattle lameness detection by using image depth data taken while cattle walking on the pathway from the milking center to the resting area. The proposed conceptual framework maps essential factors that determine lameness scores based on body movement variability. Specifically, body movement variability is to be defined as the root mean square successive differences, various types of information entropies, and geometric measures of the collected sequence of depth data during a field of depth camera view. In addition, we develop an operational simulation model that links the Monte Carlo simulation along with some popular probabilistic distribution functions such as uniform, normal, Poisson, and Gamma distributions for lameness status analysis. The simulation results lead to a conjecture that detection performance and the characteristics of lame and non-lame cows have a large influence on body movement variability. This conjecture will be realized by using real-life data in future work.
-
Gama-Markov Branching Process Approach to the Novel Coronavirus (COVID-19) Pandemic International conference
Thi Thi Zin, Pyke Tin and H. Hama
The Fifth International Symposium on Information and Knowledge Management (ISIKM2022) (onsite (Guangzhou, China / Kumamoto, Japan) and online) 2022.3.26 ICIC International
Event date： 2022.3.25 - 2022.3.26
Language：English Presentation type：Oral presentation (general)
Venue：onsite (Guangzhou, China / Kumamoto, Japan) and online
The spreads of the Novel Coronavirus (COVID-19) infectious disease have been increased exponentially in almost all countries around the world. Due to fast in transmission, big in mass and transform in variety, the world health organization has recognized the COVID-19 as a global pandemic. Since then, variety of measures such as mask wearing campaigns, social distance movements, mass vaccination programs and many others were taken globally to reduce the effective reproduction number of an infection below unity. In this paper, we propose a special type of Gama-Markov branching process model to monitor the reproduction mean rate by using data on outbreak size and outbreak duration. We develop a novel method for computing the
probabilities of the rate of spreads, outbreak sizes and outbreak duration. Some simulations based on the daily data appearing on the Internet are performed. The results show that the proposed model has promising potentials for the real-life applications. -
Predicting Calving Time of Dairy Cows by Autoregressive Integrated Moving Average (ARIMA) Model and Double Exponential Smoothing (DES) Model International conference
Tunn Cho Lwin, Thi Thi Zin and Pyke Tin
The Fifth International Symposium on Information and Knowledge Management (ISIKM2022) (onsite (Guangzhou, China / Kumamoto, Japan) and online) 2022.3.26 ICIC International
Event date： 2022.3.25 - 2022.3.26
Language：English Presentation type：Oral presentation (general)
Venue：onsite (Guangzhou, China / Kumamoto, Japan) and online
-
Cattle Face Identification with Ear Tags Using YOLOv5s Model International conference
Wai Hnin Eaindrar Mg and Thi Thi Zin
The Fifth International Symposium on Information and Knowledge Management (ISIKM2022) (onsite (Guangzhou, China / Kumamoto, Japan) and online) 2022.3.26 ICIC International
Event date： 2022.3.25 - 2022.3.26
Language：English Presentation type：Oral presentation (general)
Venue：onsite (Guangzhou, China / Kumamoto, Japan) and online
-
Black Cow Localization and Tracking with YOLOv5 and Deep SORT International conference
Cho Cho Aye, Thi Thi Zin, I. Kobayashi
The Fifth International Symposium on Information and Knowledge Management (ISIKM2022) (onsite (Guangzhou, China / Kumamoto, Japan) and online) 2022.3.26 ICIC International
Event date： 2022.3.25 - 2022.3.26
Language：English Presentation type：Oral presentation (general)
Venue：onsite (Guangzhou, China / Kumamoto, Japan) and online
Nowadays, precision livestock farming becomes popular fields in agriculture to get a high-quality product. Lacking monitoring livestock overtime can lead them to unexpectedly suffer from serious illness or even life-threatening. Therefore, individual livestock tracking systems can help to understand their actions. The proposed system is emphasized tracking individual black cows after performing cow detection. In this work, YOLOv5 (You Only Look Once) is used for detection and the Deep SORT (Simple Online Real-time Tracking) algorithm is utilized for tracking. In order to enhance the accuracy of the models, transfer learning is adopted. In the detection phase, the YOLOv5 model and appear feature model in Deep SORT were trained with a manually annotated dataset with help of transfer learning. The experimental results reveal that YOLOv5 got detection accuracy of 0.995 mAP@.5 and tracking with Deep SORT achieves the tracking accuracy of 99.4% in testing video-1 and 98.9% in testing video-2.
-
工場での作業の見える化 - 作業員のグループ識別及び追跡 - Invited
Thi Thi Zin
令和３年度先端技術研究開発促進・人材育成支援事業：IoT等先端技術利活用セミナー 2022.3.17
Event date： 2022.3.17
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
-
Action Recognition System for Senior Citizens Using Depth Image Colorization International conference
Ye Htet, Thi Thi Zin, H. Tamura, K. Kondo, E. Chosa
The 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech 2022) (Osaka, Japan) 2022.3.8 IEEE Life Sciences Technical Community
Event date： 2022.3.7 - 2022.3.9
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
This paper describes about the system which can be used at the care center for the purpose of elderly action recognition using depth camera. The depth image colorization is used for compression, visualization, and person detection process. The YOLOv5 (You Only Look Once) algorithm is used as object detector. The space-time features are extracted from depth sequences and they are recognized by linear SVM (Support Vector Machine) classifier. The random image sequences are generated for testing to recognize six actions. The results show that this system can detect the various actions with the average of 92% accuracy for different durations.
-
A Hybrid Approach: Image Processing Techniques and Deep Learning Method for Cow Detection and Tracking System International conference
Cho Cho Mar,Thi Thi Zin, I. Kobayashi, Y. Horii
The 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech 2022) (Osaka, Japan) 2022.3.8 IEEE Life Sciences Technical Community
Event date： 2022.3.7 - 2022.3.9
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
Cow detection and tracking system plays an important role in cattle farming and diary community to reduce expenses and workload. This research presents how the conventional image processing techniques can be combined with deep learning concepts to establish cow detection and tracking system. Specifically, we first employ a Hybrid Task Cascade (HTC) instance segmentation network for cow detection. We then built the multiple objects tracking (MOT) algorithm utilizing location and appearance cues (color and CNN features) to carry out cow tracking process. To leverage the robustness of the system, we also considered the recent features from the previous tracked cow.
-
A Study on Worker Tracking Using Camera to Improve Work Efficiency in Factories International conference
I. Hidaka, S. Inoue, Thi Thi Zin
The 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech 2022) (Osaka, Japan) 2022.3.8 IEEE Life Sciences Technical Community
Event date： 2022.3.7 - 2022.3.9
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
The population of Japan is declining every year. As the population declines, the number of employees in enterprises also decreases, and one of the issues for small and medium-sized enterprises is the decline in productivity due to a shortage of employees. It is necessary to improve work efficiency to compensate for the shortage of employees and the resulting decrease in productivity. If changes in the work process and unnecessary movements in the work process can be eliminated, it will lead to shortening of work time and improvement of work efficiency. In this paper, to improve work efficiency for factories, we aim to track the workers in the factory using a camera and show the trajectory of works.
-
A Study on Automatic Individual Identification of Wild Horses International conference
K. Shiiya, R. Yamada, Thi Thi Zin, I. Kobayashi
The 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech 2022) (Osaka, Japan) 2022.3.8 IEEE Life Sciences Technical Community
Event date： 2022.3.7 - 2022.3.9
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
Wild horses called "Misaki-uma" are inhabited Cape Toi in the southern part of Miyazaki Prefecture in Japan. Although wild horse, it needs health care. It is a difficult task for aging management association members to monitor the vast habitat range of horses and to identify individual during routine management. In addition, the current methods of individual identification because of contact with horses or to requiring specialized knowledge, ordinary people cannot perform it. In this paper we propose a method for automatic individual identification of wild horses without contact using an RGB camera.
-
A Deep Learning-based solution to Cattle Region Extraction for Lameness Detection International conference
Su Myat Noe, Thi Thi Zin, Pyke Tin, I. Kobayashi
The 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech 2022) (Osaka, Japan) 2022.3.8 IEEE Life Sciences Technical Community
Event date： 2022.3.7 - 2022.3.9
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
In precision livestock farming, lameness detection in cattle is particularly important for breeding management. The accurate detection of lameness is crucial for delivering effective and economical treatment and for preventing future diseases. The noticeable sign of lameness is that their speed of walking, arching their backs and drop their heads during walking. Here, we emphasis on lameness of dairy cattle by implementing the intelligent visual perception system on the laneways after milking process. Employing a deep learning technique of Mask-RCNN for cattle region detection and identification. The novelty of this work noticeably implies that deep learning instance segmentation could be effectively employed as a cattle region extraction from complex background prior to using identification and tracking.
-
An Intelligent Method for Detecting Lameness in Modern Dairy Industry International conference
Thi Thi Zin, Moe Zet Pwint, Su Myat Noe, I. Kobayashi
The 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech 2022) (Osaka, Japan) 2022.3.8 IEEE Life Sciences Technical Community
Event date： 2022.3.7 - 2022.3.9
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
Lameness is one of the major welfare concerns in the modern dairy industry. In addition, lameness makes severe health and economic problems causing losses in milk production. Although there has a sizable amount of methods, it remains some worthwhile open problems. Therefore, in this paper, we propose an intelligent method for detecting the lameness of dairy cow by establishing a visual monitoring system on the laneways after milking process. We employ a technique of Mask-RCNN for cow region extraction and utilize features based on head bob patterns. Our real-life experimental results show that the proposed method has detection accuracy of 95.5% on cow’s region extraction and can classify 80% of the lameness levels correctly.
-
Individual Identification of Cow Using Image Processing Techniques International conference
Y. Kawagoe, Thi Thi Zin, I. Kobayashi
The 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech 2022) (Osaka, Japan) 2022.3.8 IEEE Life Sciences Technical Community
Event date： 2022.3.7 - 2022.3.9
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan Country：Japan
Cow identification has become important in recent years due to outbreaks of diseases such as bovine spongiform encephalopathy. Conventional identification methods available are not efficient, affordable, non-invasive, and cost- effective. Among them, some methods are based on biological markers, such as muzzle point matching and facial recognition. Facial images are the most common biometric characteristics used by humans to identify individuals, and they have received much attention. In this study, we used RGB camera to identify individual cow by their faces and confirmed the effectiveness of this method.
-
高度な画像処理技術やAI技術を活用した研究開発 Invited
Thi Thi Zin
ICT研究開発支援セミナーin九州 (Zoom及びYouTubeによるオンライン配信) 2022.2.4 九州総合通信局
Event date： 2022.2.4
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
Venue：Zoom及びYouTubeによるオンライン配信 Country：Japan
総務省の戦略的情報通信研究開発推進事業(SCOPE)「地域ICT振興型研究開発」採択課題である「ICTを活用した牛のモニタリングシステムの開発」を中心に、「自立生活を支援するための高齢者24時間見守りシステムの開発」等の高度な画像処理技術やAI技術を活用した研究について紹介。
-
A Simple Random Walk Model for Dairy Cow Calving Time Prediction International conference
Thi Thi Zin, Pyke Tin, Pann Thinzar Seint, K. Sumi, I. Kobayashi, Y. Horii
2021 IEEE 10th Global Conference on Consumer Electronics (GCCE) (Kyoto, Japan) 2021.10.14 IEEE Consumer Technology Society
Event date： 2021.10.12 - 2021.10.15
Language：English Presentation type：Oral presentation (general)
Venue：Kyoto, Japan Country：Japan
In this paper, we propose a simple random walk model to predict time of calving event occurs for a pregnant dairy cow. Dairy farmers and experts have well recognized that an accurate calving time prediction is quite important in modern smart dairy farming. To meet these demands, we consider the number of posture changes of a pregnant cow during a few days before the expected dates as a random walk to predict the time at which the calving event occurs. For validation, we show some experimental results by using real life data collected from a large dairy farm in Japan.
-
Evaluation of the severity of tremor based on each signal acquired from the displacement of the hand movements International conference
T. Hayashida, Thi Thi Zin, K. Sakai, H. Mochizuki
2021 IEEE 10th Global Conference on Consumer Electronics (GCCE) (Kyoto, Japan) 2021.10.14 IEEE Consumer Technology Society
Event date： 2021.10.12 - 2021.10.15
Language：English Presentation type：Oral presentation (general)
Venue：Kyoto, Japan Country：Japan
Discrepancy of exam findings at the same patient make it difficult to ascertain chronological change in the disease and the efficacy of the medicine. Quantitative evaluation of severity is important for improving the discrepancy. In this study, we examine the efficacy of quantitative evaluation of tremor when using single camera. Recording the hand movements of tremor with single camera, and the displacement, velocity, and acceleration signals are acquired using the hand shift between two adjacent video frames. Quantitative evaluation of tremor is performed based on features obtained from each signal. According to the validation results, our method using single camera is possible to classify with an accuracy of up to 82.6%.
-
Cattle Region Extraction using Image Processing Technology International conference
Y. Motomura, Thi Thi Zin, Y. Horii
2021 IEEE 10th Global Conference on Consumer Electronics (GCCE) (Kyoto, Japan) 2021.10.14 IEEE Consumer Technology Society
Event date： 2021.10.12 - 2021.10.15
Language：English Presentation type：Oral presentation (general)
Venue：Kyoto, Japan Country：Japan
In recent years, the number of dairy and beef cattle farms has been decreasing, while the number of cattle and the number of cattle per farm have been increasing, so systems for automatically monitoring cattle have been actively introduced. However, most of them are contact type, which causes physical or mental stress to the cows and is costly when the equipment is damaged. Therefore, in this research, we proposed a method for extracting the approximate shape of cattle using a non-contact 360-degree camera to reduce the burden on livestock farmers and cattle, and confirmed its effectiveness through experiments.
-
Application of Methods in Sequential Analysis to Dairy Cow Calving Events International conference
Thi Thi Zin, K. Sumi, Pann Thinzar Seint, Pyke Tin, I. Kobayashi, Y. Horii
15th International Conference on Innovative Computing, Information and Control (ICICIC2021) (Online) 2021.9.15 ICIC International
Event date： 2021.9.15 - 2021.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
Apart from sequential sampling, methods in the sequential analysis have been widely and successfully used for various applications such as insurance problems, theory of storage, queuing theory, and many other stochastic models. Moreover, it is well recognized that Wald’s Fundamental Identity in sequential analysis can be used to derive approximate and some exact results in most situations wherein we have essentially a random sequence phenomenon. In this aspect, the fluctuations in motion of a pregnant cow around the calving event fall into a random sequence category. Therefore, in this paper, we explore and examine an application of Wald’s Fundamental Identity in sequential analysis to dairy cow calving time prediction models. Specifically, we will show this Fundamental Identity which can be used to derive results for predicted calving times at which an individual cow calving event occurs in a video-monitored maternity barn. The paper is pure of an expository nature and considers only simple illustrations and some real-life video data are used to confirm the proposed method.
-
Cattle Region Extraction Using Color Space Conversion International conference
Y. Hashimoto, H. Hama, Thi Thi Zin
15th International Conference on Innovative Computing, Information and Control (ICICIC2021) (Online) 2021.9.15 ICIC International
Event date： 2021.9.15 - 2021.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
The Japanese livestock industry has problems such as difficulty of finding successors of farms, and the aging farmers. Therefore, development of a cattle monitoring system through non-contact and non-invasive methods to improve productivity and reduce labor burdens is a strong desire from farmers. As one of elemental technologies to realize it, we have focused on tracking of cattle for detecting characteristic behaviors using video camera. In this paper, we present an effective extracting method of the cattle region from video images of pasture. Inter-frame difference and background subtraction are widely used for detecting moving objects in video images; however, in our case the system is supposed to be used in dusty pasture, and they do not work well. Because Japanese black cattle move slowly in general, and the skin color is similar to soil, region extraction of them is very difficult, even if these conventional methods are used. Here, region extraction using Color Space Conversion is adopted. This method enables us to manipulate easily the image’s color and automatically extract cattle region; additionally, the movement of cattle is estimated from the change of the gravity center of the extracted region. To verify the effectiveness, we carried out an experiment using the videos taken at Sumiyoshi Livestock Science Station at University of Miyazaki. The experimental results show that this method is well suited for extracting cattle region. Further verification should be conducted to enhance robustness.
-
Cow Region Segmentation in Cattle Farm by Using Semantic Segmentation Networks International conference
Swe Zar Maw, Thi Thi Zin, Pyke Tin
15th International Conference on Innovative Computing, Information and Control (ICICIC2021) (Online) 2021.9.15 ICIC International
Event date： 2021.9.15 - 2021.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
When it comes to controlling a cattle farm, being able to accurately forecast when calving will happen can be quite beneficial because it allows employees to assess whether or not assistance is required. If such help is not provided when it is required, the calving process may be prolonged, severely impacting both the mother cow and the calf’s health. Multiple diseases may result from such a delay. During the production cycle, one of the most crucial events for cows is calving. An accurate video-monitoring technique for cows can spot abnormalities or health issues early, allowing for prompt and effective human interference. To make this surveillance automated, a crucial task is to detect the cows. For this purpose, in this research, we have proposed an effective semantic segmentation network for segmenting the cow from the 360-degree surveillance camera. The proposed network is a modified version of the U-Net architecture. An additional module is added in the U-Net architecture which is named as convolutional long short-term memory (ConvLSTM) block. The ConvLSTM block allows for effective feature sharing between the less dense layers and denser layers. Experiments with our suggested method were carried out at a big dairy farm in Japan’s Oita Prefecture. The suggested method’s experimental findings demonstrate that it holds promise in real-world applications.
-
A Study on Working Group Detection after Helmet Extraction International conference
S. Inoue, I. Hidaka, Thi Thi Zin
15th International Conference on Innovative Computing, Information and Control (ICICIC2021) (Online) 2021.9.15 ICIC International
Event date： 2021.9.15 - 2021.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
Due to the declining birthrate and increasing in aging population, the industries are facing seriously with manpower shortage problems. As a consequence, many small and medium-sized factories are introducing AI and IOT to automate their operations so that they can cope with fewer employees. However, some factories are not automating because it is more economically effective to have employees perform the work directly than to automate it. Such companies can create more economic benefits with less labor by eliminating waste from their current work. In this research, we focus on the movement of people during work by using information obtained from a 4K camera installed overhead that can detect work groups and acquire data for use in creating indicators for efficiency improvement. For this purpose, we attach a marker on the top of the worker’s helmet to detect the helmet and identify the work group. The effectiveness of the proposed method has been confirmed through simulation experiments.
-
Holistically-Nested Deep Learning Model for Cow Region Detection and Motion Classification International conference
Thi Thi Zin, Saw Zay Maung Maung and Pyke Tin
15th International Conference on Innovative Computing, Information and Control (ICICIC2021) (Online) 2021.9.15 ICIC International
Event date： 2021.9.15 - 2021.9.16
Language：English Presentation type：Oral presentation (general)
Venue：Online
In dairy farming, monitoring an individual cow is a critical component for each and every aspect of precision dairy farm management system since it can make farmers and managers learn cow’s health conditions, body conditions even the occurrences of calving difficulties in times. Such monitoring is often performed visually because animal appearance and behavior are key indicators of analyzing animal conditions. According to the latest computer vision and image processing algorithms, it is now possible to implement a monitoring system that can detect the status of cows at a low cost. In this aspect, one of the important steps is to detect and segment the cows within the video sequences. Moreover, how an individual cow behaves or makes movements such as lying, standing, and changes from one posture to another is also equally important for further analysis. Therefore, in this paper, we propose a deep learning method of edge-based cow region detection and multiple linear models for the classification of cow movements. Specifically, we establish a deep learning model of holistically-nested edge detection (HED) that performs image-to-image prediction by using fully convolutional neural networks and deeply supervised nets. In the cow motion classification process, we propose multiple linear models in which the coefficients of independent variables are utilized as features for classification. According to our experimental results, the proposed detection system is promising and provides robust performance. Similar experiments are also performed to validate the proposed multiple linear models for the classification of cow motions with high accuracy.
-
Automatic Detection of Mounting Behavior in Cattle using Semantic Segmentation and Classification International conference
Su Myat Noe, Thi Thi Zin, Ikuo Kobayashi, Pyke Tin
The 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech 2021) (Nara Royal Hotel (Nara, Japan)) IEEE Life Sciences Technical Community
Event date： 2021.3.9 - 2021.3.11
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel (Nara, Japan)
In cattle farming sector, the accurate detection of estrus plays a vital role because incorrect timing for artificial insemination affects the cattle business. The noticeable sign of estrus is the standing heat, where the cattle standing to be mounted by other cows for a couple of seconds. In this paper, we proposed cattle region detection using deep learning semantic segmentation model and automatic detection of mounting behavior with machine learning classification methods. Based on the conducted experiment, the results show that a mean Intersection of Union (IoU) of 98% on the validation set. The pixel-wise accuracy for two classes (cattle and background) was found to be both 98%, respectively. For the classification, the proposed method compares the four supervised machine learning methods which can detect with the accuracy rate of Support Vector Machine, Naïve Bayes, Logistic Regression and Linear Regression are 87%, 96%, 90%, and 80% respectively. Among them, Naïve Bayes algorithm perform the best. The novelty of this work noticeably implies that deep learning semantic segmentation could be effectively employed as a pre-processing step in segmenting the cattle and background prior to using various classification models.
-
Petrochemical Characteristics of the Granitoid Rocks of Northern Myanmar International conference
Htin Lynn Aung, Thaire Phyu Win, Thi Thi Zin
The 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech 2021) (Nara Royal Hotel (Nara, Japan)) IEEE Life Sciences Technical Community
Event date： 2021.3.9 - 2021.3.11
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel (Nara, Japan)
The research area is located on the Mogaung - Kamaing-Hpakant road in Hpakant Township, Kachin State, northern Myanmar. The dominant lithologic units comprise igneous and metamorphic rocks. The present work is mainly intended to establish the petrogenesis of the igneous rocks based on the petrochemical analysis results. The igneous rocks are mainly microgranite and serpentinite. Major element analysis of some rocks was determined by XRF spectrometer and interpreted the genesis of these rock units. On the basis of the petrochemical characteristics, the microgranite of the study area is I-type peraluminous granitoid formed by partial melting of mantle and / or lower crust in the extensional tectonics.
-
Markov Chain Monte Carlo Method for the Modeling of Posture Changes Prior to Calving International conference
Thi Thi Zin, Pyke Tin, Pann Thinzar Seint, Yoichiro Horii
The 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech 2021) (Nara Royal Hotel (Nara, Japan)) IEEE Life Sciences Technical Community
Event date： 2021.3.9 - 2021.3.11
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel (Nara, Japan)
An accurate and careful analysis of posture changes for a dairy cow prior to calving plays an important role in making calving time prediction. The patterns of activities such as frequent changes in postures of a pregnant cows during the time closer to calving are utilized as indicators to predict the time of calving. In this paper, we introduce Markov Chain Monte Carlo (MCMC) method to generate the patterns of four states activities such lying, transitions from lying to standing, standing itself and transitions from standing to lying based on the monitored cow activity changes data three days prior to calving. The validity of the generated cow activities in posture changes data is compared with the actual collected data in terms of Euclidean and Cosine distance measures. The experimental results show that the method in this paper can be used as a generalized method to generate synthetic data series of dairy cow activities prior to calving.
-
Image Technology Based Detection of Infected Shrimp in Adverse Environments International conference
Thi Thi Zin, Takehiro Morimoto, Naraid Suanyuk, Toshiaki Itami, Chutima Tantikitti
The 1st International Conference on Sustainable Agriculture and Aquaculture: For Well Being and Food Security (Prince of Songkla University) www.psu.ac.th, www.kku.ac.th, www.ku.ac.th, www.cmu.ac.th,
Event date： 2021.1.11 - 2021.1.12
Language：English Presentation type：Oral presentation (general)
Venue：Prince of Songkla University
In recent years, the cultivation of white leg shrimp (Litopenaeus vannamei) has become popular in countries around Japan, especially in Southeast Asia, and at the same time, various diseases have occurred in the farms [1]. In the early stages of infection, shrimp show three abnormal behaviors: (1) they appear in the shallow waters of the farm, (2) they do not move and do not eat even when fed, and (3) they suddenly start moving. Early detection is important step to control this disease because there are no preventive measures. In addition, we are currently visually confirming shrimp that show characteristic of the disease. However, these lead to a burden on the farmers and delay in discovery [2]. Therefore, we propose an image technology based monitoring system for detecting shrimp showing the characteristics of diseases.
-
Consumer Behavior Analyzer in Internet of Things (IoT) Environments International conference
Swe Nwe Nwe Htun, Thi Thi Zin and Pyke Tin
4th International Symposium on Information and Knowledge Management (ISIKM2020) (Online Conference) ICIC International
Event date： 2020.12.12 - 2020.12.13
Language：English Presentation type：Oral presentation (general)
Venue：Online Conference
This paper proposes an analyzer of consumer behavior in Internet of Things (IoT) environments. This analyzer is most useful in predicting the intentions of users during searches, and especially during image searches. Since most technologies are connected on the internet, search results can be characterized using image-similarity measures. In this paper, information on image similarities is extracted using a Convolutional Neural Network (CNN) in IoT environments. In this proposed consumer behavior analyzer, the similarity measures characterizing the relationships between images are transformed into Markov Chain transition probabilities, and their stationary probabilities are then analyzed to describe the priority order for search results conforming with consumer intentions. In order to confirm the validity of the proposed method, the Yelp public dataset was used. The outcomes using this analyzer are promising, and this analyzer might be instrumental in making further improvements in practical applications of consumer technologies.
-
Systematic Inclusion Study on Some Rare Gemstones of the Mogok Area, Mandalay Region, Myanmar International conference
Htin Lynn Aung, Thaire Phyu Win and Thi Thi Zin
4th International Symposium on Information and Knowledge Management (ISIKM2020) (Online Conference) ICIC International
Event date： 2020.12.12 - 2020.12.13
Language：English Presentation type：Oral presentation (general)
Venue：Online Conference
In this paper we shall explore and examine an inclusion aspect of some rare gemstones of Mogok area which is known as the Ruby Land of Myanmar where 90% of world rubies come from. The materials presented in this paper are the products of our research team investigated some rock sequences in the Mogok area situated about 280 miles north of the capital Naypyidaw, has unearthed some of the rarest and most luxurious rubies including the legendary 82-carat Nga Mauk ruby discovered centuries ago.. The rock sequence of the study area consists of medium to high grade metamorphic rocks, marble, gneiss and intrusive igneous rocks, mainly Kabaing granite, leucogranite and syenite. It is famous for presence of ruby and sapphire. Exceptionally some rare gemstones are also discovered. The present work is mainly intended to describe systematically the inclusions of some rare gemstones from the Mogok area. Liquid feather inclusions present in jeremejevite. Two-phase inclusions occur in morganite and petalite. In petalite, tube-like inclusions also present. Opaque inclusion and solid inclusion occur in rutile and treacle granular inclusion and finger print inclusion observe in sinhalite.
-
Smart Irrigation: An Intelligent System for Growing Strawberry Plants in Different Seasons of the Year International conference
Ye Htet, Htin Kyaw Oo and Thi Thi Zin
4th International Symposium on Information and Knowledge Management (ISIKM2020) (Online Conference) ICIC International
Event date： 2020.12.12 - 2020.12.13
Language：English Presentation type：Oral presentation (general)
Venue：Online Conference
Agriculture is an important source of livelihood and varying the way of cultivating plants could provide more productivity and sustainability of foods than before and thus smart irrigation would be one of the best solutions. Therefore, the proposed system mainly focused on the strawberry plants to grow within small-scale farm using intelligent systems to bear and produce fruits in all seasons of the country. A challenging problem which arises for this objective is the precise temperature, water and fertilizer management for plants. So, this system emphasized on automatic environmental adjustment system integrated with sensors to control temperature and also drip irrigation system for efficient water and fertilizers usage. Moreover, leaf analysis using computer vision which is controlled by Raspberry Pi is implemented for detection of the nutrient deficiency symptoms of plants. As for the communication unit to inform the users via sensors and image processing, Internet of Things is adopted.
-
Dam Water Overflow Estimation using Time Series International conference
Mie Mie Khin, Mie Mie Tin, Thi Thi Zin, Pyke Tin
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE) (Kobe, Japan) IEEE
Event date： 2020.10.13 - 2020.10.16
Language：English Presentation type：Oral presentation (general)
Venue：Kobe, Japan
This paper will implement the water level estimation of the dam from Myanmar. We use the time series stochastic model to calculate the water level estimation varying on in flow and consumption of dam. This approach is applying probability of Markovian Time Series. This paper based on rainfall and the other factors of dam water storage such as inflow and outflow of dam. This result estimate actual monthly water spread area and shows error is small. This research result also highlight that Markovian Time Series model is one of the best estimate processes for water level estimation.
-
Predicting Calving Time of Dairy Cows by Exponential Smoothing Models International conference
Tunn Cho Lwin, Thi Thi Zin, Pyke Tin
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE) (Kobe, Japan) IEEE
Event date： 2020.10.13 - 2020.10.16
Language：English Presentation type：Oral presentation (general)
Venue：Kobe, Japan
In dairy farming, calving time prediction is crucial because the calf loss rate during calving time is rising for many reasons. In this paper, we propose a time series model with exponential smoothing technique to predict the time of calving event occurs. By investigating the changes in behavior patterns a few days before the calving events, the proposed method can predict accurately the time of occurrence of calving events. To be specific, we model the number of changes in behaviors of standing and lying as a time series in hourly basis. We then employ the exponential smoothing techniques and survival probability with exponential distribution to make the prediction process. To confirm the proposed method, some experimental works are performed by using video records of 25 cows in calving pen from a large farm at Oita prefecture, Japan.
-
Detection of Estrus in Cattle by using Image Technology and Machine Learning Methods International conference
Su Myat Noe, Thi Thi Zin, Pyke Tin, Hiromitsu Hama
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE) (Kobe, Japan) IEEE
Event date： 2020.10.13 - 2020.10.16
Language：English Presentation type：Oral presentation (general)
Venue：Kobe, Japan
Detection of estrus in cattle in early phase is especially vital in the era of precision farming. This paper focuses on the detection of estrus in cattle by using image processing techniques and machine learning methods. In doing so, we first utilize an image analysis to investigate some behaviors of cattle in estrus, which is standing when mounted by the other cattle. We then extract some statistical measures based on polyline shape features of detected cattle images and utilize these measures as an input to machine learning algorithms. Specifically, in this paper, we employ the three supervised machine learning methods, which is Support Vector Machine (SVM), Logistic Regression (LR), and Multiple Linear Regression (MLR) classifiers. Some experimental works are performed by using real-life video sequences. The results show promising and capable to detect the behavior of estrus both cost-effectively (only image) and specifically with the detection rate of SVM is 97%, LR is 94%, and MLR is 94%, respectively.
-
Image Processing and Statistical Analysis Approach to Predict Calving Time in Dairy Cows International conference
Swe Zar Maw, Thi Thi Zin, Pyke Tin
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE) (Kobe, Japan) IEEE
Event date： 2020.10.13 - 2020.10.16
Language：English Presentation type：Oral presentation (general)
Venue：Kobe, Japan
An accurate prediction of calving time in dairy cows is one of the most important factors to make an optimal reproduction process in dairy farming. This paper proposes an image processing and statistical analysis approach to predict calving time in dairy cows. Specifically, we extract the behavior changes patterns of the expected cows by using simple effective motion history images (MHI) a few days before the occurrence of calving event from the video sequences taken in the maternity bans. We then classify extracted features with support vector machine (SVM) and analyze the behavior changes by using statistical method, Hidden Markov model (HMM) for prediction process. To confirm the validity of proposed method, we perform some experiments by installing 360-degree view cameras at the top of calving bans. At the first stage, we analyzed the behaviors of 25 dairy cows for 72 hours before giving birth. As a result, we find that the proposed method is promising.
-
Feature Detection and Classification of Cow Motion for Predicting Calving time International conference
Thi Thi Zin, Saw Zay Maung Maung, Pyke Tin, Yoichiro HORII
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE) (Kobe, Japan) IEEE
Event date： 2020.10.13 - 2020.10.16
Language：English Presentation type：Oral presentation (general)
Venue：Kobe, Japan
The monitoring and automatic detecting of cow behaviors is a key factor for predicting cow calving times. This paper describes the analysis of cow motion patterns by using 360 camera in order to identify various views of cow states. Firstly, Principle Component Analysis (PCA) is applied to solve the rotation variant problem in different postures of cow body and then the dominant features (shape distances) are extracted for cow motion classification such as Standing, Lying, and Transition States (Standing-to-Lying and Lying-to-Standing). During the movement of cow motions, the increasing and decreasing trends of shape (Beta features) from cow body are used to classify transition activities of cows. We prepared the datasets by grouping similar motion sequences and tested against with the proposed features. According to experimental results, the proposed system can give the high accuracy with low computational cost in case of detecting and classifying cow motions.
-
A Mobile Application for Offline Handwritten Character Recognition International conference
Thi Thi Zin, Moe Zet Pwint, Shin Thant
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE) (Kobe, Japan) IEEE
Event date： 2020.10.13 - 2020.10.16
Language：English Presentation type：Oral presentation (general)
Venue：Kobe, Japan
The handwritten character recognition is a computerized system that is able to identify and recognize characters and words written by user. In this paper, we proposed offline handwritten character recognition using deep learning architecture. The Android application of the proposed system is also created by using OpenCV and TensorFlow Lite. The proposed system is aimed to use as a teaching aid in helping kindergarten to primary school level students, especially for practicing their writing and learning. The local handwritten dataset, which includes digit, English alphabet and mathematical symbols that are collected from students, is used for training and testing operations. According to the experimental results, the proposed system is very promising and it will be a useful application for educational environment.
-
Elderly Monitoring and Action Recognition System Using Stereo Depth Camera International conference
Thi Thi Zin, Ye Htet, Yuya Akagi, Hiroki Tamura, Kazuhiro Kondo, Sanae Araki
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE) (Kobe, Japan) IEEE
Event date： 2020.10.13 - 2020.10.16
Language：English Presentation type：Oral presentation (general)
Venue：Kobe, Japan
The proposed system used stereo type depth camera by examining the human action recognition and also sleep monitoring in the elderly care center. Different regions of interest (ROI) are extracted using the U-Disparity and V-Disparity maps. The main information used for recognition is 3D human centroid height relative to the floor and percentage of movement from frame differencing for sleep monitoring. The results from the experiments of the proposed method show that this system can detect the person location, sitting or lying and also sleep behaviors effectively.
-
画像処理技術を用いた牛のモニタリングシステム Invited
Thi Thi Zin, 小林 郁雄, 椎屋 和久, PYKE TIN, 堀井 洋一郎, 濱 裕光
電気・情報関係学会九州支部連合大会 （第７３回連合大会） (オンライン開催 （大会本部：九州産業大学）) 電気・情報関係学会九州支部連合大会委員会
Event date： 2020.9.26 - 2020.9.27
Language：Japanese Presentation type：Oral presentation (general)
Venue：オンライン開催 （大会本部：九州産業大学）
高齢化、大規模化する現代の畜産で、24時間 365日にわたり家畜の健康管理を適切に行い、異常や変化に注意し続けながら経営を継続することは容易ではない。本研究開発では、家畜生産性の向上と地域活性化の実現を目的とする牛のモニタリングシステム構築に必要な要素技術の開発を行う。ここでは、牛の体脂肪率の指標となる BCS（Body Condition Score)を、画像解析技術を用いて自動的に評価し、その経時変化から健康状態をモニタリングできるシステムに関する開発について発表する。
-
Interdisciplinary Approach to Smart Dairy Farming Invited International conference
Thi Thi Zin
The 3rd University Conference on Science, Engineering and Research, 2020 (3rd UCSER, 2020) (Technological University ( Kyaukse), Myanmar) Ministry Of Education Deportment Of Higher Education, Technological University ( Kyaukse)
Event date： 2020.8.27
Language：English Presentation type：Oral presentation (invited, special)
Venue：Technological University ( Kyaukse), Myanmar
Smart dairy farming emerged from the concept of Precision Agriculture, in which IoT technologies and artificial intelligence analysis are put to efficient use. Using these technologies to provide individual care for cows is fundamental to the future of dairy farming. Most dairy farms around the globe adhere to international ISO standards in identifying individual cows. On the other hand, 5G communications are being developed widely and nicely making the dairy farming smarter and faster in wealth and health. Thus, the dairy farming in agriculture should be explored from the perspectives of engineering disciplines. In this talk, we shall focus on how image processing techniques can be utilized to develop a tracking system for individual cows using an ear tag visual analysis.
-
Time To Dairy Cow Calving Event Prediction by Using Time Series Analysis International conference
Thi Thi Zin, Kosuke Sumi, Pyke Tin
The 9th International Conference on Intelligent Computing and Applications (ICICA 2020) (Brisbane, Australia) Central Queensland University, Dalian University of Technology (DUT),National Tsing Hua University, Swinburne University of Technology, University of Technology Sydney, University of Wollongong, Australia
Event date： 2020.6.23 - 2020.6.25
Language：English Presentation type：Oral presentation (general)
Venue：Brisbane, Australia
In these days the precision dairy farming which is utilization of the Information and Communication Technologies (ICT) has become one of front line research topics in dairy science as well as in data science leading to Agriculture 4.0. An increase in on-farm mortality due to the occurrence calving difficulties with late assistance can cause possible problems not only for animal welfare but also economic losses to the farmers. In this aspect, calving is an extremely important event in the life of a dairy cow. On the other hand, the time around calving is also a critical period since clinical disorders, and calving problems can occur. Calving difficulties are also becoming increasingly common with many dairy cows requiring assistance at the time of calving. To maximize welfare and minimize losses due to calving difficulties, all animals need to be individually monitored to identify any calving difficulties or health problems as early as possible. In addition, it is important to know the exact time of calving event occur so that timely assistance can be made. In this paper, we propose a continuous video monitoring system for time-to calving event investigation based on time series analysis to achieve an accurate calving time prediction. In doing so we have employed three time series models of autoregressive, moving average smoothing. At the same time, we have confirmed the validity of the proposed method by using the real life data experimented on the University Dairy Farm and one of large dairy farms in Japan. The experimental results show that the proposed time series method is promising and can lead to a new prospect in modern precision dairy farming.
-
Framework of Cow Calving Monitoring System Using Video Images International conference
Kosuke Sumi, Thi Thi Zin, Ikuo Kobayashi, Yoichiro Horii
The 9th International Conference on Intelligent Computing and Applications (ICICA 2020) (Brisbane, Australia) Central Queensland University, Dalian University of Technology (DUT),National Tsing Hua University, Swinburne University of Technology, University of Technology Sydney, University of Wollongong, Australia
Event date： 2020.6.23 - 2020.6.25
Language：English Presentation type：Oral presentation (general)
Venue：Brisbane, Australia
In modern dairy farms, calving is a very critical point in the life cycle of productive cows and has played a major role in making farm profits and welfare of cows. In this time, a tremendous number of researchers have been studied the problem of calving mostly to predict the time about to calve and to investigate calving process by using wearable sensors. Like human beings, cows also have environmental pressures by wearing sensors on their bodies sometimes may cause calving difficulties. Thus in this paper, an automatic video based cow monitoring system is proposed to reduce losses of dairy farms caused from calving problems. Specifically, this paper investigates some behaviors of cows to predict time for calving process including cow movements, tail up, stretching the legs, repeating standing and sitting. In doing so, we focus on increasing movement and tail up. Here, the inter-frame difference is used for analyzing the movement and count in every frame. In addition, by extracting the head and tail position the activity of tail up or not will be recognized so that time for calving can be estimated. Finally, the proposed method for calving is confirmed by using self-collected video sequences.
-
Body Condition Score Assessment of Depth Image using Artificial Neural Network International conference
Thi Thi Zin, Pann Thinzar Seint, Pyke Tin, Yoichiro Horii
The 9th International Conference on Intelligent Computing and Applications (ICICA 2020) (Brisbane, Australia) Central Queensland University, Dalian University of Technology (DUT),National Tsing Hua University, Swinburne University of Technology, University of Technology Sydney, University of Wollongong, Australia
Event date： 2020.6.23 - 2020.6.25
Language：English Presentation type：Oral presentation (general)
Venue：Brisbane, Australia
Body Condition Score (BCS) is a visual sign for managing feeding program. It can be described by numeric numbers to estimate available fat reserves and it also allows producers to make better management decisions. Ignoring BCS until it becomes too thin or fat may result in production and animal losses economically. In this paper, we proposed the BCS assessment tool by using depth information from 3D camera. The experimental data were collected in Oita prefecture and BCS scores were taken under the guidance of experts. The information of depth images are used as feature vectors to the input of Artificial Neural Network (ANN) classifier. The proposed system has achieved the good results for classifying two groups of BCS (3.5 and 3.75) with the overall accuracy of 86%.
-
Cow Identification System using Ear Tag Recognition International conference
Thi Thi Zin, S. Misawa, Moe Zet Pwint, Shin Thant, Pann Thinzar Seint, K. Sumi, K. Yoshida
The 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2019) (Mielparque Kyoto (Kyoto, Japan)) IEEE Life Sciences Technical Community
Event date： 2020.3.10 - 2020.3.12
Language：English Presentation type：Oral presentation (general)
Venue：Mielparque Kyoto (Kyoto, Japan)
In precision dairy farming, the valid record of individual cow identification is an important factor in large herds management. In this paper, we propose a cow's ear tag recognition system that can be used in dairy cow management. Firstly, cow's head detection is performed by using You Only Look Once (YOLO) object detector followed by ear tag recognition. The ear tag extraction and recognition processes are carried out by image processing techniques and Convolutional Neural Network (CNN) classifier on detected cow's head images. The experiments are conducted by using videos from dairy farm at Hokkaido prefecture, Japan. The proposed system achieved the reliable results which will support to give the informative status in smart farming.
-
Motion Detection Method for Reducing Foreground Aperture Problem in Background Modelling International conference
Thi Thi Zin, Pyke Tin, Cho Nilar Phyo
The 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2019) (Mielparque Kyoto (Kyoto, Japan)) IEEE Life Sciences Technical Community
Event date： 2020.3.10 - 2020.3.12
Language：English Presentation type：Oral presentation (general)
Venue：Mielparque Kyoto (Kyoto, Japan)
Motion detection plays as an important role in the implementation of video surveillance system and video analysis applications. The detection of moving foreground objects from the complex background scene is the first step in most of the computer vision based surveillance applications. In this paper, we present a new motion detection method using background modelling technique and moving average feature. For establishing the robust background model, we create the Gamma Mixture Model based on the Gamma distribution function. For handling the foreground aperture problem, we use the feature called moving average which can well recognize the alive silent objects. As post-processing, we handle the shadow removing process by generating the dynamic shadow threshold. The experimental results show that the proposed motion detection method can detect the accurate foreground object even though the foreground object appears as silent background objects in real-time environment.
-
Handwritten Characters Segmentation using Projection Approach International conference
Thi Thi Zin, Shin Thant, Ye Htet, Pyke Tin
The 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2019) (Mielparque Kyoto (Kyoto, Japan)) IEEE Life Sciences Technical Community
Event date： 2020.3.10 - 2020.3.12
Language：English Presentation type：Poster presentation
Venue：Mielparque Kyoto (Kyoto, Japan)
In the area of optical character recognition, handwritten character segmentation is still an ongoing process. Having good segmentation result can provide the better recognition accuracy. In the proposed system, segmentation is carried out mainly on labelling and projection concepts. The input word is firstly labelled. Then, the modified word is segmented with projection approach. The experiments are performed on local dataset with 1600 words approximately and the system gets segmentation accuracy around 85.75 percentage.
-
The Body Condition Score Indicators for Dairy Cows Using 3D Camera International conference
Thi Thi Zin, Pann Thinzar Seint, Pyke Tin, Y. Horii
International Workshop on Frontiers of Computer Vision (IW-FCV) (Ibusuki, Kagoshima, Japan) Institute of Electrical Engineers of Japan
Event date： 2020.2.20 - 2020.2.22
Language：English Presentation type：Oral presentation (general)
Venue：Ibusuki, Kagoshima, Japan
Body Condition Score (BCS) evaluates energy reserves of cows when making nutritional management. This information is also useful in fertili-ty rate and milk production. Keeping cows in appropriate condition throughout the production cycle can improve reproductive efficiency and positive impact for economics. In this paper, we propose the effective indicators for automated BCS measurement system and the experimental data are collected at the milk-ing station. We compute the variation of angular area from automatic anatom-ical point extraction and learning parameters on Region of Interest (ROI) from 3D information. The statistical analysis of BCS trend on year-round data are presented to give the detailed illustrations for dairy farmers. According to the recorded BCS trends, the proposed method can validate that the lower BCS were obtained in early stage of lactation period rather than other seasons.
-
Background Modelling Using Temporal Average Filter and Running Gaussian Average International conference
Thi Thi Zin, Cho Cho Mar, K. Sumi
International Workshop on Frontiers of Computer Vision (IW-FCV) (Ibusuki, Kagoshima, Japan) Institute of Electrical Engineers of Japan
Event date： 2020.2.20 - 2020.2.22
Language：English Presentation type：Poster presentation
Venue：Ibusuki, Kagoshima, Japan
Object detection is very important and fundamental stage for further post processing stages such as individual identification, action recognition, track-ing and behavior analysis. Traditional object detection methods start from back-ground modelling stage. Background modelling is a complex and challenging task which highly depends on the speed of moving objects (foreground objects) and stability of static regions (background region). In this paper, we proposed pixel level background modelling method. In this background modelling task, the two main components of background modelling are proposed; (1) background model initialization by selecting the dynamic frames from video sequence and building the model with Temporal Average filter and (2) updating the back-ground model by using Running Gaussian Average method. These methods are applied to RGB images.
-
Some Aspects of Mathematical Modeling Techniques in Dairy Science International conference
Thi Thi Zin, Pyke Tin, H. Hama
International Workshop on Frontiers of Computer Vision (IW-FCV) (Ibusuki, Kagoshima, Japan) Institute of Electrical Engineers of Japan
Event date： 2020.2.20 - 2020.2.22
Language：English Presentation type：Poster presentation
Venue：Ibusuki, Kagoshima, Japan
Today world is floating in the ocean of data science which is a multi-disciplinary approach to every aspect of our better life. Agriculture 4.0 is coming in and Industry 4.0 is moving forward so that second Information and Commu-nication revolutionary becomes to play a key role in this era. On the other hands, consumers are demanding more quality dairy products than before. Dairy farmers are eager to use the information and communication technologies that push the precision dairy farming to frontier innovations. Due to a shortage of labor in dairy farms and at the same time the farm sizes are bigger, the utilization of ICT along with artificial intelligence and the internet of things are becoming appropriate technologies. Whatever it may be, fundamentally we need to do some preliminary research prior to large scale and wide applications to the real world. In almost analytical and empirical research, we are trying in the ocean of data science. These data could not be used efficiently unless we do further processing and pro-jections. The raw data need to be processed to obtain useful information and knowledge, which could be used for important on-farms decisions. This kind of process is called mathematical modeling which could support to decision-makers to produce correct and valid decisions. In this paper, we will present and analyze some mathematical models in the frame works of dairy science. Moreover, we shall illustrate how these models could be used in practical ways.
-
Feature Analysis for Non Formal Education Project in Myanmar International conference
Mie Mie Khin, Mie Mie Tin, Thi Thi Zin, Pyke Tin
2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2018) (Senri Life Science Center, Osaka, Japan) IEEE Consumer Electronics Society
Event date： 2019.10.15 - 2019.10.18
Language：English Presentation type：Oral presentation (general)
Venue：Senri Life Science Center, Osaka, Japan
In a digitally mediated world, Literacy is vital to live. IT based Digital technology is the creation of quality education. It is the main pillar to develop a sustainable socioeconomic development in the country. Myanmar also starts to develop E-government system for every sector. This paper describes feature selection for non-formal education system using literacy project. With this approach, we consider that feature selection of linear regression the analysis is more suitable than support vector method. We are also continuing analysis of this e-education system for rural area in Mandalay division of Myanmar. This paper analysis based on big data concept.
-
Consumer Technology Perspective of a Trinomial Random Walk Model International conference
Thi Thi Zin, Pyke Tin, H. Hama
2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2018) (Senri Life Science Center, Osaka, Japan) IEEE Consumer Electronics Society
Event date： 2019.10.15 - 2019.10.18
Language：English Presentation type：Oral presentation (general)
Venue：Senri Life Science Center, Osaka, Japan
Recently, the consumer technology association has widened the horizons of the consumer electronic society to include a variety of technologies such as the Internet of Things, Artificial Intelligence, vertical farming and etc. Moreover, among many others, the consumer technology highlights the importance of organic dairy cows and they are well beings so that timely based energy balance and body condition scores of individual cows are needed to be thoroughly studied. In this paper, we shall introduce a Trinomial Random Walk Model as an illustration of consumer technology for analyzing changes in dairy cow body conditions from time to time. In doing so, we will use the 5-point scale system with increment 0.25. Some experimental simulation results are presented by varying the parameters involved.
-
Motion History and Shape Orientation Based Human Action Analysis International conference
Swe Nwe Nwe Htun, Thi Thi Zin
2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2018) (Senri Life Science Center, Osaka, Japan) IEEE Consumer Electronics Society
Event date： 2019.10.15 - 2019.10.18
Language：English Presentation type：Oral presentation (general)
Venue：Senri Life Science Center, Osaka, Japan
In recent decades, many research works focused on the considerations of falling and post-falling event analysis in the aspect of image processing technology to meet the consumer perspective of users. In this paper, the more informative considerations of human action analysis are developed for the prior state of fall or normal actions. In doing so, the effective background subtraction namely the Mixture of Gaussian with Low-Rank Matrix Factorization model is used to obtain robust and adaptive foreground from the practical video sequences. Then, the spatial-temporal bilateral grid for video sequences is constructed by using a standard graph cut theory to improve the cleaned foreground in order to detect the moving/motionless object region. Then, human actions are analyzed by employing motion history and shape orientation using the approximated ellipse method. The experiments are conducted on publicly available video sequences and our simulated video sequences.
-
Image-Based Feeding Behavior Detection for Dairy Cow International conference
K. Shiiya, F. Otsuka, Thi Thi Zin, I. Kobayashi
2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2018) (Senri Life Science Center, Osaka, Japan) IEEE Consumer Electronics Society
Event date： 2019.10.15 - 2019.10.18
Language：English Presentation type：Oral presentation (general)
Venue：Senri Life Science Center, Osaka, Japan
Feeding behavior is an important source of information to know cow's health status, because it is influenced by the feeding environment, cow's physiological changes and health conditions. However, a cow feeds intermittently throughout the day, it is difficult to measure feeding time by visual measurement at field level. In this paper we propose a measurement method of feeding frequency and feeding time for dairy cow, by detecting the feeding behavior by non-contact using a camera.
-
ICTを活用した牛のモニタリングシステムの開発に関する研究 Invited
Thi Thi Zin、小林 郁雄、椎屋 和久、Pyke Tin、堀井 洋一郎、濱 裕光
2019年度電気・情報関係学会九州支部連合大会（第72回連合大会） (九州工業大学 戸畑キャンパス) 電気・情報関係学会
Event date： 2019.9.27 - 2019.9.28
Language：Japanese Presentation type：Oral presentation (general)
Venue：九州工業大学 戸畑キャンパス
高齢化、大規模化する現代の畜産で、24 時間 365 日に
わたり家畜の健康管理を適切に行い、異常や変化に留意
し続けながら経営を継続することは容易でない。本研究で
は、家畜生産性の改善と地域活性化の実現を最終目的と
する。人の監視・見守りの分野で開発された非接触・非侵
襲センサ情報の解析アルゴリズムを独自の手法で応用し、
生産者の負担を大幅に軽減しながら家畜の状態を 24 時間
監視できるシステムを開発する。具体的には、畜産農家か
らの強い要望がある、ボディコンディションスコア（BCS：Body Condition Score）の評価、発情検知、分娩過程の管理、個体識別、異常検知等を可能とするシステムの開発を目指す。 -
Gemological Analysis of Some Rare Gemstones from Mogok Area, Mandalay Region International conference
Htin Lynn Aung, Thi Thi Zin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
Mogok has long been noted as a supplier of various gemstones over the past decades. The principal gemstones are ruby, sapphire and spinel. Nowadays, fabulous rare gemstones from Mogok are being sold in foreign markets. This area is mainly composed of igneous and metamorphic rocks. Exceptionally rare gemstones are also discovered and they are johachidolite, poudretteite, thorite, etc. The fantastic occurrences of rare gemstones provoke attraction and well attention to mineralogists and gemmologists. Most of the rare gemstones in the present research work are studied from gems dealers from Mogok. Other rare samples are recorded and studied in the favour of the gems collectors. The data on primary occurrence of these rare gemstones are still uncertain and further investigation should be required. In the Mogok area, these rare minerals recovered from alluvial, eluvial, residual deposits along the river side, hill slope, flat plains and low lying area. Economically, rare gemstones are highly important for both local and foreign gem markets. Some gemstones are important economically as well as technologically for its composition, such as thorite and beryl which are used in space and aeronautical purposes. Most of the rare gemstones are valuable for its rarity and collected as museum pieces and collector’s stones. Thus, they are invaluable.
-
Robust Tracking of Cattle Using Super Pixels and Local Graph Cut for Monitoring Systems International conference
Y. Hashimoto, H. Hama, Thi Thi Zin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
Development of a cattle monitoring system by non-contact and non-invasive methods to improve productivity is a strong desire from large or small scale farmers with aging society. As one of elemental technologies, we will focus on estimating the position of cattle for detecting characteristic behaviors using video camera frames. To do so, cattle region must be extracted. Because Japanese black cattle move slowly in general, region extraction by the inter-frame difference is difficult. At the same time, since the skin is similar to soil in color, region extraction is not so easy, even if background subtraction is used. Here, ROI (Region of Interest) and Scribbles (foreground, background) are manually set at first, and SP (Super Pixels) and LGC (Local Graph Cut) are adopted to extract robustly cattle regions. The movement of cattle is estimated from change of the gravity center of the extracted cattle region. We propose a new method to update ROI and Scribbles according to the change. The tracking of cattle walking normally was successfully continued until a part of the body was framed out. Without proposed updating, there are many cases in which tracking fails within a few frames. The effectiveness of the proposed method has been confirmed through the experimental results.
-
A Correlated Random Walk Modeling Method for Dairy Cow Inter-calving Body Condition Score Pattern Analysis International conference
Thi Thi Zin, Pyke Tin, H. Hama
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
In this paper, we shall explore and examine the potentials of a correlated random walk model to describe the body condition score pattern change between two successive calving time intervals in dairy cows. The random walk model due to its stochastic natures can fully describe the pattern and quantify its characteristics composed of the sum of random variables derived from milk yields, feeding intakes and transition periods in the body energy reserves changes. In order to achieve optimality of dairy farm management systems, the key indicator is individual cow body conditions score for maintaining target score in corresponding periods such as a few weeks after calving, early lactation, mid lactation and dry periods. Thus, the dairy cow energy reserves problem of within-the-two successive calving events, the body condition score fluctuations is critical especially at the time of calving, with improvements in production. However, a little has known the statistical and probabilistic tools for relating the body condition score pattern change and milk production, feeding management and animal health during the inter-calving periods. In this concern, we shall formulate the problem of energy reserves in dairy cow body, as a correlated random walk model in which inputs (feed intakes), outputs (mike produced) and the body condition score (energy research storage) are used as random variables. Utilizing an incomplete Gamma and the univariate normal distribution functions for the marginal and joint distributions of the inputs and outputs in the random walk model, the expected change patterns in body condition scores with respect to time are derived and analyzed. Then we provide some simulation results by using the estimated parameters for inputs and outputs derived from real life dataset. These results shows that the proposed approach and method are promising in line with precision dairy farming.
-
Offline Handwritten Character Recognition System on Tablet Mobile International conference
Thi Thi Zin, T. Otsuzuki
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
Handwritten character recognition is one of the most challenging and important research areas in the field of image processing since there is a variation of same character due to the change of fonts and sizes in handwriting especially by early learners in formal and non-formal basic education. The early school age children in general have diversity in handwriting style, variation in angle, size and shape of characters making the problems of character recognition more difficult. In recent years, due to international efforts, the number of enrolled students worldwide has been increasing year by year. However, due to lack of teachers, many children cannot access high quality education. Therefore, in this paper, offline character recognition for handwritten characters written on tablet was proposed. This paper can be expected to support education for preschool children. This proposed method firstly performs character segmentation process on words acquired from the tablet. In the feature extraction proposes Histogram of Oriented Gradients (HOG) and Bag-of-Visual Words (BOVW) are used. Support Vector Machine (SVM) is applied in classification process. Some experimental results are shown to confirm the proposed method.
-
A Study on Detecting Violence Using Image Processing Technology International conference
S. Misawa, Thi Thi Zin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
In recent years, many security cameras have been installed for crime prevention in downtown areas and public facilities. These cameras have greatly contributed to crime prevention and criminal identification. However, the large number of installed cameras is problematic due to difficulties in manually monitoring and detecting violence and crime in real time, as well as in finding specific video footage recording the incidents. This paper describes the use of the background difference method in extracting human regions from data obtained using security cameras. In addition, the paper describes a method of detecting violence using features such as speed and moving distance after contact. Using video footage from seven data sets, these methods have been experimentally evaluated, confirming a high detection rate for incidents involving two people side by side.
-
Object Tracking Based on Color Features from Key Frames International conference
Mie Mie Tin, Mie Mie Khin, Nyein Nyein Myo, Thi Thi Zin, Pyke Tin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
In the world, everybody needs to protect their life to save and to prevent from dangerous case. Some case cannot protect for life, such as accident case on the road, the criminal case and so on. It says that need to give some information to them that is never emancipate from the criminal case and never find bolt-hold. This system can support like case, because system processes under the security surveillance camera network and use all video files from that camera network. These videos are extracted as frames based on time and relevant frames are stored as frame sequence. The system extracts key information frames from that frames sequence with relevant time. The system handles all important key information frames and extract important object using colour features base and collects the path of that object by tracking of different background region. To track selected object, the system collects all key information frames from videos in a network with time base. The selected importance key object is searched other information key frames. To search selected object from other key frames, the system use object segmentation on colour features.
The user needs to select tracking objects from key frames a video. That selected important object is extracted feature values based on RGB features and HSV hue value. This research tests on private dataset, surveillance camera network, from Myanmar Institute of Information Technology University (MIIT), Mandalay, Myanmar. All surveillance cameras are configured at the different stable places and camera view is stable in vision. That camera network has 85 cameras totally and used HIKVISION network bullet camera and HIKVISION E series Network Speed Dome camera. This research is ongoing stage and five members are working as a group. -
An Algebraic Geometric Imaging Approach for Automatic Dairy Cow Body Condition Scoring System International conference
Thi Thi Zin, Pyke Tin, I. Kobayashi, and Y. Horii
2019 International Conference on Precision Dairy Farming Technologies and Applications (Tokyo, Japan) World Academy of Science, Engineering and Technology
Event date： 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Tokyo, Japan
In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.
-
Multivariate Stochastic Analyzer for Dairy Cow Body Condition Scoring International conference
Thi Thi Zin, K. Sumi, Pyke Tin
International Conference on Digital Image and Signal Processing (DISP 2019) (Oxford University, UK)
Event date： 2019.4.29 - 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Oxford University, UK
In this paper, we introduce a conceptual multivariate stochastic analyzer for assessing body condition scores of individual dairy cows. Specifically, by using digital image technologies and statistical stochastic methods, dairy cow body condition scoring machine is to be established. In modern precision dairy farming, the body condition score (BCS) plays an important role as an indicator for measuring health and wealth of a dairy farm. Based on the BCS, today dairy farm manage systems are improved in in various aspects such as milk production, right time for artificial insemination, prediction calving time and so on. Traditionally, human experts perform visual examinations on the key areas of cow body parts such as hook, pin bones, tail head, short ribs, and backbone starches for scoring. However, well-trained human experts become less and dairy farm sizes are bigger as a consequence manual body condition scoring is almost impractical. Thus, in this paper we propose an image technology based stochastic analyzer for automatic scoring the BCS measures of dairy cows. In order to do so, the proposed analyzer first extracts some key anatomical points of a cow by using two-dimensional images taken from top views. Then, the system will derive some distance and angular features of the anatomical points and employs stochastic sampling techniques for refining the extracted features to produce parameters of multiple regressive prediction models and to assess the body condition scores of all dairy cows in the farm. Finally, to confirm the validity of proposed analyzer, we perform some experiments by a well-known benchmark dataset. The experimental results seem to be promising with an impact of high accuracy.
-
Incorporating Digital Imaging in Dairy Cow Anatomical Feature Detection International conference
Thi Thi Zin, Cho Nilar Phyo, Pyke Tin
International Conference on Digital Image and Signal Processing (DISP 2019) (Oxford University, UK)
Event date： 2019.4.29 - 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Oxford University, UK
In today precision dairy farming, the most commonly used technologies include wearable devices which must be attached to cows in one way or another in order to monitor cow’s behaviors. Since the wearable sensors placements may be broken or lost and can burden additional stress to the cows, it is necessary to consider an alternative and effective non-contact monitoring system. For this purpose, digital imaging technologies are suitable due to their capabilities of continuous operation and able to full automation. Thus, in this paper, we propose a digital imaging approach based on topological persistence concepts to precision dairy cow monitoring system focused on automated dairy cow anatomical feature detection. Anatomically these features define as hips, hooks, pin bones, tail-heads and rear regions of the cow body. These features will be utilized in the decision making process if and where a cow is present in an image or video frame. Once the system detects a cow in the image, the system automatically identifies an individual cow. The proposed cow anatomical feature detection and cow identification have the potentials in detecting cow body conditions, health conditions in time, milk production trends and predicting calving time and heat occurrence. Finally, by using videos taken in a real-life cow farm, the experimental results confirm the validity of proposed method.
-
Dairy Cow Body Conditions Scoring System Based on Image Geometric Properties International conference
Thi Thi Zin, Pyke Tin, Ikuo Kobayashi
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
In modernized precision dairy farming, the importance of dairy cow body condition scores is well recognized for making the healthy, wealthy and optimizing milk production. Although a burst amount of researches have been investigated the condition scoring problems from various aspects, not much satisfactory results have been come out yet. So, this paper will propose a geometric imaging approach for an automatic dairy cow body conditions scoring system. Specifically, some significant land marks or anatomical points are to be extracted from the top view image of a cow and their geometrical properties such as angles, length and area are investigated to estimate body condition scores. In doing so, the proposed method will employ techniques of polynomial regression, multiple regression, Markov Chain classification. Finally, some experimental results will be presented by using self-collected datasets and some well-known public datasets. The performance of preliminary results shows promising so that the approach of proposed method can lead to be applicable in real life environments.
-
OCR Perspectives in Mobile Teaching and Learning for Early School Years in Basic Education International conference
Thi Thi Zin, Swe Zar Maw, Pyke Tin
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
In these days, teaching and learning systems in schools with the use of mobile or portable devices such as tablets, e-readers, smartphones are becoming keen interests of educators as well as parents and teachers in worldwide. In this aspect, the early years of school children in basic education are the most challenging and important in developing effective and quality education for life. Since they are quite young and unable to dedicate time the need for easy to use and effective learning aids has become vital. Especially their writing skills are somehow needed to be improved with encouragements. In order to do so, the handwritten of characters and numerals performed by the children especially those living in less developing countries should be correctly recognized so that means and ways for remedies and solutions for improvements could be found. Thus the optical character recognition techniques for handwritten alphabets and numerals are moving into front especially the handwritten of children of early years in schools. In this paper, we introduce a Mobile Tutor - an effective and correct way of character segmentation and recognition of messy and unclear handwritten characters to help children learn and practice handwriting and early numeric operations such as addition and subtraction as well as help teachers monitor and review children’s progress. Some experiments are performed by providing tablets to the users and collecting handwritten characters from the users for recognition and analysis.
-
A Study on Detection of Precursor Behaviors of Estrus in Cattle Using Video Camera International conference
Hiromitsu Hama, Tetsuya Hirata, Tsubasa Mizobuchi, Thi Thi Zin
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
Development of an estrus detection system by non-contact and non-invasive methods to improve productivity is a strong desire from livestock farmers with aging society. As one of the elemental technologies, we will focus on detecting precursor behaviors of estrus in cattle using video camera. First, we converted from two-dimensional motion on video image to three dimensional one. Next, some features which are well-known as estrus precursor behaviors, were selected, for example, walking speed, trajectory and relative positional relationship of two cattle. Through experimental results, we could confirm the effectiveness of our proposed algorism. As the result, although it is a small case, it was able to detect without any false positive and false negative.
-
Innovations of Digital Imaging in Smart Dairy Farming Invited International conference
Thi Thi Zin
The 17th International Conference on Computer Applications (ICCA 2019) and The 11th International Conference on Future Computer and Communication (ICFCC 2019) (Novotel Hotel, Yangon, Myanmar) University of Computer Studies, Yangon
Event date： 2019.2.27 - 2019.3.1
Language：English Presentation type：Oral presentation (invited, special)
Venue：Novotel Hotel, Yangon, Myanmar
-
Framework of Cow Calving Monitoring System Using a Single Depth Camera International conference
K. Sumi, Thi Thi Zin, I. Kobayashi, Y. Horii
International Conference Image and Vision Computing New Zealand (IVCNZ 2018) (Auckland, New Zealand) IEEE Advancing Technology for Humanity (Technically co-sponsor)
Event date： 2018.11.19 - 2018.11.21
Language：English Presentation type：Poster presentation
Venue：Auckland, New Zealand
Calving difficulty is the primary cause of the problem of increasing death loss in cow-calf. It also profoundly effects on the economic impact of farmers and producers because of calves' death, injury to cows and high veterinary cost. To help the calving difficult of cows in time, long time continuous monitoring is required for deciding when and how to assist the calving process of cows. On the other hand, the continuous monitoring of cows' welfare become the major burden task for labors especially in a large farm where has a large number of cows. Therefore, the demands of sophisticated technology for automatic monitoring of cows' welfare is more and more increasing every year. In recent years, some researcher develops the automatics monitoring and predicting the cows' calving behavior by using the sensors devices such as temperature sensors and acceleration sensors. However, the sensors based system has various problems such as spalling and malfunction of the sensors and even can cause the burden on the cow because sensors are needed to put inside or on the body of the cow. To overcome those problems, in this paper, we propose an automatic detection of cows' calving behavior by using the depth camera (3D camera) along with image processing and computer vision technology and coordinate system transformation concept. The proposed system by using 3D camera can reduce the burden of both labors and cows.
-
A Hybrid Rolling Skew Histogram-Neural Network Approach to Dairy Cow Identification System International conference
Cho Nilar Phyo, Thi Thi Zin, H. Hama, I. Kobayashi
International Conference Image and Vision Computing New Zealand (IVCNZ 2018) (Auckland, New Zealand) IEEE Advancing Technology for Humanity (Technically co-sponsor)
Event date： 2018.11.19 - 2018.11.21
Language：English Presentation type：Poster presentation
Venue：Auckland, New Zealand
In this paper, we propose a hybrid method in which rolling skew histogram and neural network techniques are fused to recognize patterns and identify cows in the milking rotary parlor of dairy farms. Individual cow identification is very important for managing the welfare and health care of an individual cow and developing the body condition scoring system. Although there has some sensor-based cows' identification system, those systems require to attach the sensor devices on each cow which is costly and burden on the cows. Since the proposed method applies a single video camera which is a non-contact device for the identification of many different cow patterns, the proposed system is low cost and no burdens on the cow. In particular, the operation of the system takes place while the cows are in the milking process in rotary milking parlor where the monitoring of individual cow is more effective than some other time and places. The identification process is based on the black and white pattern on the cow's body while moving on the rotary milking parlor. For the detecting and cropping of cows' body region is carried out by using rolling the skew histogram and used for the training process of the deep convolutional neural network. The trained network is employed for the identification of individual cow in the testing process. The experiments are performed on the self-collected cow video dataset which includes around 60 different cow's body patterns that have been taken at the large-scale farm in Oita Prefecture, Japan. The experimental results show that the proposed system is promising with the overall accuracy of 96.3 % and it is very effective and practical for the real-time cow identification system needed for establishing a modern precision dairy farming.
-
An Image Technology Approach to Dairy Cow Monitoring System Invited International conference
Thi Thi Zin
National Symposium on Livestock Research and Development 2018, The Faculty of Animal Science, Universitas Gadjah Mada (Universitas Gadjah Mada, Yogyakarta, Indonesia) The Faculty of Animal Science, Universitas Gadjah Mada
Event date： 2018.11.5
Language：English Presentation type：Oral presentation (invited, special)
Venue：Universitas Gadjah Mada, Yogyakarta, Indonesia
-
ICTを活用した牛のモニタリングシステムの開発に関する研究 Invited
Thi Thi Zin, 小林 郁雄、椎屋 和久、PYKE TIN、堀井 洋一郎、濱 裕光
九州ＩＣＴイノベーションセミナー2018 (アクロス福岡) 総務省九州総合通信局、（一社）九州テレコム振興センター（KIAI）
Event date： 2018.11.2
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
Venue：アクロス福岡
-
暮らしを快適に変える画像処理技術 Invited
Thi Thi Zin
Yumenavi LIVE 2018、学問の講義ライブ (マリンメッセ福岡) FROMPAGE
Event date： 2018.10.20
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
Venue：マリンメッセ福岡
-
A Study on Abnormal Behavior Detection of Infected Shrimp International conference
Takehiro Morimoto, Thi Thi Zin, Toshiaki Itami
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
A method of detecting infected shrimp has been developed. Though shrimp production is thriving in Japan, disease causes much damage. Because the cause is a virus infection, medical treatment is not currently possible. The infection route includes factors such as predation by environmental organisms and water-borne infection. However, no specific countermeasures have been developed. Therefore, early detection of infected shrimp is necessary to prevent secondary infection. When shrimp are infected, they exhibit the following abnormal behaviors: 1) not eating, 2) appearing in shallow water, or 3) making sudden movements. The developed method of detecting infected shrimp involves the use of image processing to determine when the shrimp are not eating.
-
A Study on Non-contact and Non-invasive Neonatal Jaundice Detection and Bilirubin Value Prediction International conference
Sojiro Kawano, Thi Thi Zin, Yuki Kodama
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
Neonatal jaundice is a yellowish discoloration of skin and eyes that commonly occurs in newborn babies. It is a physiological phenomenon in neonates and it occurs due to the overproduction of bilirubin, reduction of bilirubin treatment function. The quick and accurate treatment is required for neonatal jaundice because it can lead to nuclear jaundice, cerebral palsy, intellectual disturbance and various sequelae. The investigation methods for examining neonatal jaundice include examination using jaundice meter and blood sampling. However, these methods require continuous monitoring and can cause burden on newborn babies. In this paper, we propose the non-contact and non-invasive detection method for neonatal jaundice using image processing and computer vision technology. The experiments are performed on the data collected by University Hospital, University of Miyazaki. According to the experiments, we confirmed about the usefulness of proposed method which can work effectively for infants.
-
An Automatic Estimation of Dairy Cow Body Condition Score Using Analytic Geometric Image Features International conference
Thi Thi Zin, Pyke Tin, I. Kobayashi, Y. Horii
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
In today modern precision dairy farms, among many dominant factors the Body Condition Score (BCS) has been considered a critical value to optimize milk production, analyzing health problems, insemination timing, and many others. Currently, the BCS is measured by human experts giving time- consuming and varying outcomes from one expert to another so that an automatic estimation system for body condition scoring is needed to be developed. Although there have been some researchers on the topics of the BCS by using image processing techniques, an efficient and satisfactory method has not been found yet. Therefore, in this paper, a new approach to an automatic estimation of dairy cow BCS using analytic geometry image features will be considered. Some experimental results are shown by using the BCS database.
-
A Study on Detection and Tracking of Estrous Behaviors for Cattle Using Laser Range Sensor and Video Camera International conference
Tsubasa Mizobuchi, Thi Thi Zin, Ikuo Kobayashi, Hiromitsu Hama
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
Nowadays, the methodology of cattle production has been transferred from natural mating to artificial insemination. Therefore, estrous detection for cattle is very important to determine the time period that farmers conduct artificial insemination. However, the observation of estrous behavior by human's eyes through the whole day become as a burden task when the number of cattle is large. Therefore, most farmers are missing to notice estrous behavior. In this paper, we proposed the method for automated detection of cattle's estrous behavior, which is mounting and standing, by using laser range sensor and image processing technology. Some experiments are carried out at the Sumiyoshi field, Faculty of Agriculture, University of Miyazaki. Through experimental results, the effectiveness of our proposed method was confirmed.
-
Medication and Meal Intake Monitoring using Human-Object Interaction International conference
Pann Thinzar Seint, Thi Thi Zin, Mitsuhiro Yokota
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
Needs for end-of-life care are rising because of increasing age-related challenges. Among them, maintenance of nutrition and medication play an important role in healthcare of elderly people. In this situation, caregivers need to receive the daily record as a trending of usage which will lead to improvements in the quality of care. Our objective is to establish a video monitoring system for the act of taking medication and eating activity which is designed by using human-object interaction. For the evaluation of medication intake scenario, we propose the hierarchical classification system using hybrid PRNN-SVM model for action classification and activity interpretation. By the contribution of rulebased learning, our system also recognizes drinking/eating activity.
-
最新の画像処理技術と畜産およびセキュリティシステムへの応用 Invited International conference
Thi Thi Zin
The 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018) (シーガイアコンベンションセンター (Miyazaki, Japan)) IEEE SMC Society
Event date： 2018.10.7 - 2018.10.10
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
Venue：シーガイアコンベンションセンター (Miyazaki, Japan)
-
暮らしを快適に変える画像処理技術の進歩 Invited
Thi Thi Zin
第２回理系女子支援講座、宮崎県立宮崎北高等学校 (宮崎県立宮崎北高等学校) 宮崎県立宮崎北高等学校
Event date： 2018.9.8
Language：Japanese Presentation type：Oral presentation (invited, special)
Venue：宮崎県立宮崎北高等学校
-
Ranking of Influential users based on User-Tweet bipartite graph International conference
Radia EL BACHA, Thi Thi Zin
2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI 2018) (Furama RiverFront Hotel, Singapore) IEEE Singapore RFID Chapter and IEEE Singapore ITSS Chapter
Event date： 2018.7.31 - 2018.8.2
Language：English Presentation type：Oral presentation (general)
Venue：Furama RiverFront Hotel, Singapore
Today, even if we are still geographically situated, but real-time news and trends are able to reach us no matter how far we are or how huge is the time difference. This is due to Social Networks Services and the strong involvement of people to them through posting, sharing and interacting online with information. Therefore, we propose a study on patterns of information diffusion on Twitter during global scale events. We also introduce a method for identifying influencers and quantify popularity of Tweets on the Network based on a user-tweet bipartite graph.
-
A study on detection of abnormal behavior by a surveillance camera image International conference
Hiroaki Tsushita, Thi Thi Zin
1st International Conference on Big Data Analysis and Deep Learning (ICBDL 2018) (Phoenix Seagaia Resort, Miyazaki, Japan ) University of Miyazaki, Springer Verlag
Event date： 2018.5.14 - 2018.5.15
Language：English Presentation type：Oral presentation (general)
Venue：Phoenix Seagaia Resort, Miyazaki, Japan
At present, an enormous amount of accidents and terrorisms has been occurred all over the world not only Japan. Due to the spread of security cameras, the number of occurrences of theft and robbery incidents has been decreasing more and more. Nonetheless, the arrest rate has not improved so much and improvement and rising of the arrest rate are required. The objective of this paper is detection of snatching that involves an event between two persons, and we made an effort to detect snatching in various kinds of situations by using some video scenarios. This video scenarios include the scene of snatching with a bicycle and the scene of non-snatching with normal pedestrian passing. Our proposed methods consist of several steps: background subtraction, pedestrian tracking, feature extraction, and snatch theft detection. We focused on the feature extraction process in details and used weighted decision fusion system based on these parameter, area feature, motion feature, and appearance feature in the paper [1]. We attempted to detect the snatching event from diverse features.
-
A study on detection of suspicious persons for intelligent monitoring system International conference
Tatsuya Ishikawa, Thi Thi Zin
1st International Conference on Big Data Analysis and Deep Learning (ICBDL 2018) (Phoenix Seagaia Resort, Miyazaki, Japan ) University of Miyazaki, Springer Verlag
Event date： 2018.5.14 - 2018.5.15
Language：English Presentation type：Oral presentation (general)
Venue：Phoenix Seagaia Resort, Miyazaki, Japan
Currently, surveillance cameras are proliferating for prevention of crimes worldwide and early detection of emergency situations, and they play a very important role in the field of crime prevention and verification against various crimes. With regard to crime recognition and crime arrest, the number of surveillance cameras has been on the rise since it became widespread, and this has also led to crime prevention. However, in most cases, it will be coped after the occurrence of crime, and as for ongoing surveillance for 24 h, the burden on the surveillance side is heavy and there are cases where suspicious people are overlooked. In this paper, by focusing on the action of “Loitering” performed by a criminal using various characteristics of a person, it is possible to automatically determine whether the target person is a “Normal Pedestrian” or “Suspicious Pedestrian”. We will develop algorithms to make it recognizable and confirm the usefulness in terms of crime prevention and crime verification. It is also expected that establishing detection technology will contribute to crime reduction as a deterrent against crime.
-
A study on music retrieval system using image processing International conference
Emi Takaoka, Thi Thi Zin
1st International Conference on Big Data Analysis and Deep Learning (ICBDL 2018) (Phoenix Seagaia Resort, Miyazaki, Japan ) University of Miyazaki, Springer Verlag
Event date： 2018.5.14 - 2018.5.15
Language：English Presentation type：Oral presentation (general)
Venue：Phoenix Seagaia Resort, Miyazaki, Japan
The music retrieval system has made it possible to easily search music by simply listening to songs on machine with the spread of smartphone applications. However, it requires enormous data by voice information existing system. Therefore, we proposed new music retrieval system using images visualized by sound signal processing. In the experiment, we used 35 songs and made data for retrieval by extracting a part from them and using only melody information. As a result, the percentage of correct answers that appeared in the top 3 places was 89%, which proved that the proposed method is useful.
-
A study on violence behavior detection system between two persons International conference
Atsuki Kawano, Thi Thi Zin
1st International Conference on Big Data Analysis and Deep Learning (ICBDL 2018) (Phoenix Seagaia Resort, Miyazaki, Japan ) University of Miyazaki, Springer Verlag
Event date： 2018.5.14 - 2018.5.15
Language：English Presentation type：Oral presentation (general)
Venue：Phoenix Seagaia Resort, Miyazaki, Japan
Lately, surveillance cameras have been widely used for security concerns to monitor human behavior analysis by using image processing technologies. In order to take into accounts for human rights, costs effectiveness, accuracy of performance the systems so that an automatic—human behavior analytic system shall be developed. –In particular, this paper focused on the action of two person violence and detecting two person fighting each other will be considered. Some experimental results are presented to confirm the proposed method by using ICPR 2010 Contest on Semantic Description of Human Activities (SDHA 2010) dataset.
-
A survey on influence and information diffusion in twitter using big data analytics International conference
Radia El Bacha, Thi Thi Zin
1st International Conference on Big Data Analysis and Deep Learning (ICBDL 2018) (Phoenix Seagaia Resort, Miyazaki, Japan ) University of Miyazaki, Springer Verlag
Event date： 2018.5.14 - 2018.5.15
Language：English Presentation type：Oral presentation (general)
Venue：Phoenix Seagaia Resort, Miyazaki, Japan
By now, even if we are still geographically situated, we’re able to reach, connect and know about each other through social networks like never before. Among all popular Social Networks, Twitter is considered as the most open social media platform used by celebrities, politicians, journalists and recently attracted a lot of attention among researcher mainly because of its unique potential to reach this large number of diverse people and for its interesting fast-moving timeline where lots of latent information can be mined such as finding influencers or understanding influence diffusion process. This studies have a significant value to various applications, e.g., understanding customer behavior, predicting flu trends, event detection and more. The purpose of this paper is to investigate the most recent research methods related to this topic and to compare them to each other. Finally, we hope that this summarized literature gives directions to other researchers for future studies on this topic.
-
A study on estrus detection of cattle combining video image and sensor information International conference
Tetsuya Hirata, Thi Thi Zin, Ikuo Kobayashi, Hiromitsu Hama
1st International Conference on Big Data Analysis and Deep Learning (ICBDL 2018) (Phoenix Seagaia Resort, Miyazaki, Japan ) University of Miyazaki, Springer Verlag
Event date： 2018.5.14 - 2018.5.15
Language：English Presentation type：Oral presentation (general)
Venue：Phoenix Seagaia Resort, Miyazaki, Japan
In Japan, the detection rate of estrus behavior of cattle has declined from 70% to 55% in about 20 years. Causes include the burden of the monitoring system due to the aging of livestock farmers and oversight of detection of estrus behavior by multiple rearing. Because the time period during which estrus behavior appears conspicuously is nearly the same at day and night, it is necessary to monitor on a 24-h system. In the method proposed in this paper, region extraction of black cattle is performed by combining frame difference and MHI (Motion History Image), then feature detection of count formula is performed using the characteristic and features of the riding behaviors. In addition, as a consideration of the model experiment, a method of detecting the riding behavior by combining the vanishing point of the camera and the height from the foot of the cattle was proposed. The effectiveness of both methods were confirmed through experimental results.
-
Behavior Analysis for Nursing Home Monitoring System International conference
Pann Thinzar Seint, Thi Thi Zin
1st International Conference on Big Data Analysis and Deep Learning (ICBDL 2018) (Phoenix Seagaia Resort, Miyazaki, Japan ) University of Miyazaki, Springer Verlag
Event date： 2018.5.14 - 2018.5.15
Language：English Presentation type：Oral presentation (general)
Venue：Phoenix Seagaia Resort, Miyazaki, Japan
In this paper, we describe the nursing home monitoring system based on computer vision. This system is aimed for an effective and automatic take care of aged persons to monitor appropriate medication intake. Skin region detection for mouth and hand tracking and color label detection for water and medication bottles tracking are mainly performed for initialization. To differentiate the hand and face region, we use the regional properties of head with online learning. Tracking is done by the minimum Eigen values detection. The overlapping area ratios of desired object to body parts are simply used as feature vectors and Pattern Recognition Neural Network is proposed for the decision of simplest action. This paper presents the 7 types of simple actions recognition for medication intake and our experimental results give the promising results.
-
A Study on Disease Diagnosis by Tremor Analysis International conference
Yuichi Mitsui, Nobuyuki Ishii, Hitoshi Mochizuki, Thi Thi Zin
The 26th International MultiConference of Engineers and Computer Scientists (IMECS 2018) (Hong Kong) The International Association of Engineers (IAENG)
Event date： 2018.3.14 - 2018.3.16
Language：English Presentation type：Oral presentation (general)
Venue：Hong Kong
-
Markov Chain Techniques for Cow Behavior Analysis in Video-based Monitoring System International conference
Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Hiromitsu Hama
The 26th International MultiConference of Engineers and Computer Scientists (IMECS 2018) (Hong Kong) The International Association of Engineers (IAENG)
Event date： 2018.3.14 - 2018.3.16
Language：English Presentation type：Oral presentation (general)
Venue：Hong Kong
-
Image Technology based Cow Identification System Using Deep Learning International conference
Thi Thi Zin, Cho Nilar Phyo, Pyke Tin, and Hiromitsu Hama, Ikuo Kobayashi
The 26th International MultiConference of Engineers and Computer Scientists (IMECS 2018) (Hong Kong) The International Association of Engineers (IAENG)
Event date： 2018.3.14 - 2018.3.16
Language：English Presentation type：Oral presentation (general)
Venue：Hong Kong
-
Interdisciplinary Perspectives for Life-Nature and Society Development Invited International conference
Thi Thi Zin
International Symposium on the Development of Life- Unfolding with interdisciplinary views @ University of Miyazaki (University of Miyazaki) University of Miyazaki
Event date： 2017.12.11
Language：English Presentation type：Oral presentation (invited, special)
Venue：University of Miyazaki
-
画像処理を用いた2者間における暴力検知に関する研究
河野 敦紀，Thi Thi Zin
第19回日本知能情報ファジィ学会九州支部学術講演会 (鹿児島大学) SOFT九州支部
Event date： 2017.12.2
Language：Japanese Presentation type：Oral presentation (general)
Venue：鹿児島大学
-
Some characteristics of nanyaseik area corundum and other assorted gemstones in Myanmar International conference
Htin Lynn Aung, Thi Thi Zin
The 11th International Conference on Genetic and Evolutionary Computing (ICGEC2017) (Kaohsiung, Taiwan) Fujian University of Technology, National University of Kaohsiung, Harbin Institute of Technology, others
Event date： 2017.11.6 - 2017.11.8
Language：English Presentation type：Oral presentation (general)
Venue：Kaohsiung, Taiwan
-
Markov Queuing Theory Approach to Internet of Things Reliability International conference
Thi Thi Zin, Pyke Tin, Hiromitsu Hama
The 11th International Conference on Genetic and Evolutionary Computing (ICGEC2017) (Kaohsiung, Taiwan) Fujian University of Technology, National University of Kaohsiung, Harbin Institute of Technology, others
Event date： 2017.11.6 - 2017.11.8
Language：English Presentation type：Oral presentation (general)
Venue：Kaohsiung, Taiwan
-
A New Conceptual Model for Big Data Analysis International conference
Thi Thi Zin, Pyke Tin, Hiromitsu Hama
The 11th International Conference on Genetic and Evolutionary Computing (ICGEC2017) (Kaohsiung, Taiwan) Fujian University of Technology, National University of Kaohsiung, Harbin Institute of Technology, others
Event date： 2017.11.6 - 2017.11.8
Language：English Presentation type：Oral presentation (general)
Venue：Kaohsiung, Taiwan
-
Exploring Gemstones in Northern Part of Myanmar International conference
Htin Lynn Aung, Thi Thi Zin
The 11th International Conference on Genetic and Evolutionary Computing (ICGEC2017) (Kaohsiung, Taiwan) Fujian University of Technology, National University of Kaohsiung, Harbin Institute of Technology, others
Event date： 2017.11.6 - 2017.11.8
Language：English Presentation type：Oral presentation (general)
Venue：Kaohsiung, Taiwan
-
Skeleton Motion History based Human Action Recognition Using Deep Learning International conference
Cho Nilar Phyo, Thi Thi Zin, Pyke Tin
The 6th 2017 IEEE Global Conf. on Consumer Electronics (GCCE2017) (Nagoya, Japan) IEEE Consumer Electronics Society
Event date： 2017.10.24 - 2017.10.27
Language：English Presentation type：Oral presentation (general)
Venue：Nagoya, Japan
-
Nanyaseik ruby of phakant township, Kachin state, northern Myanmar International conference
Htin Lynn Aung, Thi Thi Zin
The 6th 2017 IEEE Global Conf. on Consumer Electronics (GCCE2017) (Nagoya, Japan) IEEE Consumer Electronics Society
Event date： 2017.10.24 - 2017.10.27
Language：English Presentation type：Oral presentation (general)
Venue：Nagoya, Japan
-
Epitome key information extraction using color values on block International conference
Mie Mie Tin, Nyein Nyein Myo, Mie Mie Khin, Thi Thi Zin, Pyke Tin
The 6th 2017 IEEE Global Conf. on Consumer Electronics (GCCE2017) (Nagoya, Japan) IEEE Consumer Electronics Society
Event date： 2017.10.24 - 2017.10.27
Language：English Presentation type：Oral presentation (general)
Venue：Nagoya, Japan
-
A study on cow monitoring system for calving process International conference
Kosuke Sumi, Thi Thi Zin, Ikuo Kobayashi, Yoichiro Horii
The 6th 2017 IEEE Global Conf. on Consumer Electronics (GCCE2017) (Nagoya, Japan) IEEE Consumer Electronics Society
Event date： 2017.10.24 - 2017.10.27
Language：English Presentation type：Oral presentation (general)
Venue：Nagoya, Japan
-
Automatic Evaluation of Cow's Body-Condition-Score Using 3D Camera International conference
Sosuke Imamura, Thi Thi Zin, Ikuo Kobayashi, Yoichiro Horii
The 6th 2017 IEEE Global Conf. on Consumer Electronics (GCCE2017) (Nagoya, Japan) IEEE Consumer Electronics Society
Event date： 2017.10.24 - 2017.10.27
Language：English Presentation type：Oral presentation (general)
Venue：Nagoya, Japan
-
A Markov Chain Approach to big data ranking systems International conference
Radia El Bacha, Thi Thi Zin
The 6th 2017 IEEE Global Conf. on Consumer Electronics (GCCE2017) (Nagoya, Japan) IEEE Consumer Electronics Society
Event date： 2017.10.24 - 2017.10.27
Language：English Presentation type：Oral presentation (general)
Venue：Nagoya, Japan
-
A study on automatic display system of the archery score for the visually impaired International conference
Kazuhisa Shiiya, Thi Thi Zin, Misaki Jomoto, Hitoshi Watanabe
The 6th 2017 IEEE Global Conf. on Consumer Electronics (GCCE2017) (Nagoya, Japan) IEEE Consumer Electronics Society
Event date： 2017.10.24 - 2017.10.27
Language：English Presentation type：Oral presentation (general)
Venue：Nagoya, Japan
-
Classification of Shape Images Using K-mean Clustering and Deep Learning International conference
Swe Zar Maw, Thi Thi Zin, Mitsuhiro Yokota, Ei Phyo Min
12th International Conference on Innovative Computing, Information and Control (ICICIC2017) (Kurume, Japan) ICIC International
Event date： 2017.8.28 - 2017.8.30
Language：English Presentation type：Oral presentation (general)
Venue：Kurume, Japan
-
An Innovative Deep Machine for Human Behavior Analysis International conference
Thi Thi Zin, Pyke Tin, Hiromitsu Hama
12th International Conference on Innovative Computing, Information and Control (ICICIC2017) (Kurume, Japan) ICIC International
Event date： 2017.8.28 - 2017.8.30
Language：English Presentation type：Oral presentation (general)
Venue：Kurume, Japan
-
招待講演: 畜産業における画像処理・認識技術の応用研究に関する話題 Invited
Thi Thi Zin
SOFT九州支部夏季ワークショップ2017in 指宿 (休暇村指宿) 日本知能情報ファジィ学会九州支部
Event date： 2017.8.24 - 2017.8.25
Language：Japanese Presentation type：Oral presentation (invited, special)
Venue：休暇村指宿
画像処理・認識技術はIOT（モノのインターネット）の進展と共に，多方面で活用されるようになってきた．その一例として，牛のモニタリングシステムの開発に関する技術動向を紹介する．高齢化，大規模化する現代の畜産で，24時間365日にわたり家畜の健康管理を適切に行い，異常や変化に留意し続けながら経営を継続することは容易でない．人的負担軽減のための自動モニタリングシステムの開発は，畜産農家からの強い要望がある．ICT（情報通信技術）を活用し，家畜生産性の改善と地域活性化の実現を目指した各方面での取り組みの現状を紹介する．また，本講演では，私たちの研究グループでの取り組みについても紹介する．
-
Estimating body condition score of cows from images with the newly developed approach International conference
Nay Chi Lynn, Zin Mar Kyu, Thi Thi Zin, Ikuo Kobayashi
2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) (Kanazawa, Japan) IEEE and ACIS
Event date： 2017.6.26 - 2017.6.28
Language：English Presentation type：Oral presentation (general)
Venue：Kanazawa, Japan
-
ホルスタインの白黒模様を用いた個体識別
高松 聖之、Thi Thi Zin、小林 郁雄
画像処理応用および画像処理一般、電気学会知覚情報/次世代産業システム合同研究会 (宮崎大学、宮崎市、日本) 非整備環境現場に駆動されたパターン認識技術協同研究委員会，スマートビジョン実利用化協同研究委員会，知覚融合センシング技術の実利用化協同研究委員会
Event date： 2017.3.26 - 2017.3.27
Language：Japanese Presentation type：Oral presentation (general)
Venue：宮崎大学、宮崎市、日本
-
3Dカメラを用いた牛のBCS予測システムの構築
今村 颯介、Thi Thi Zin、小林 郁雄
画像処理応用および画像処理一般、電気学会知覚情報/次世代産業システム合同研究会 (宮崎大学、宮崎市、日本) 非整備環境現場に駆動されたパターン認識技術協同研究委員会，スマートビジョン実利用化協同研究委員会，知覚融合センシング技術の実利用化協同研究委員会
Event date： 2017.3.26 - 2017.3.27
Language：Japanese Presentation type：Oral presentation (general)
Venue：宮崎大学、宮崎市、日本
-
牛の分娩監視における行動解析に関する研究
須見 公祐、Thi Thi Zin、小林 郁雄
画像処理応用および画像処理一般、電気学会知覚情報/次世代産業システム合同研究会 (宮崎大学、宮崎市、日本) 非整備環境現場に駆動されたパターン認識技術協同研究委員会，スマートビジョン実利用化協同研究委員会，知覚融合センシング技術の実利用化協同研究委員会
Event date： 2017.3.26 - 2017.3.27
Language：Japanese Presentation type：Oral presentation (general)
Venue：宮崎大学、宮崎市、日本
-
Visual Monitoring System for Elderly People Daily Living Activity Analysis International conference
Thi Thi Zin, Pyke Tin, and Hiromitsu Hama
The 25th International MultiConference of Engineers and Computer Scientists (IMECS 2017) (Hong Kong) The International Association of Engineers (IAENG)
Event date： 2017.3.15 - 2017.3.17
Language：English Presentation type：Oral presentation (general)
Venue：Hong Kong
-
Human Identification using X-Ray Image Matching International conference
Ryudo Ishigami, Thi Thi Zin, Norihiro Shinkawa, Ryuichi Nishii
The 25th International MultiConference of Engineers and Computer Scientists (IMECS 2017) (Hong Kong) The International Association of Engineers (IAENG)
Event date： 2017.3.15 - 2017.3.17
Language：English Presentation type：Oral presentation (general)
Venue：Hong Kong
-
Color and Shape based Method for Detecting and Classifying Card Images International conference
Cho Nilar Phyo, Thi Thi Zin, Hiroshi Kamada, Takashi Toriu
The 2017 International Conference on Artificial Life and Robotics (ICAROB 2017) (Miyazaki, Japan) ICAROB Society(ALife Robotics Corporation Ltd.)
Event date： 2017.1.19 - 2017.1.22
Language：English Presentation type：Oral presentation (general)
Venue：Miyazaki, Japan
-
An effective method for detecting snatch thieves in video surveillance International conference
Hiroaki Tsushita, Thi Thi Zin
The 2017 International Conference on Artificial Life and Robotics (ICAROB 2017) (Miyazaki, Japan) ICAROB Society(ALife Robotics Corporation Ltd.)
Event date： 2017.1.19 - 2017.1.22
Language：English Presentation type：Oral presentation (general)
Venue：Miyazaki, Japan
-
Automatic Assessing Body Condition Score from Digital Images by Active Shape Model and Multiple Regression Technique International conference
Nay Chi Lynn, Thi Thi Zin, Ikuo Kobayashi
The 2017 International Conference on Artificial Life and Robotics (ICAROB 2017) (Miyazaki, Japan) ICAROB Society(ALife Robotics Corporation Ltd.)
Event date： 2017.1.19 - 2017.1.22
Language：English Presentation type：Oral presentation (general)
Venue：Miyazaki, Japan
-
Automatic Target Tracking System based on Local and Global Features International conference
Thi Thi Zin, Kenshiro Yamada
The 10th International Conference on Genetic and Evolutionary Computing (ICGEC2016) ( Fuzhou City, Fujian Province, China) Fujian University of Technology, Springer, others
Event date： 2016.11.7 - 2016.11.9
Language：English Presentation type：Oral presentation (general)
Venue： Fuzhou City, Fujian Province, China
-
Deep Learning Model for Integration of Clustering with Ranking in Social Networks International conference
Thi Thi Zin, Pyke Tin, Hiromitsu Hama
The 10th International Conference on Genetic and Evolutionary Computing (ICGEC2016) ( Fuzhou City, Fujian Province, China) Fujian University of Technology, Springer, others
Event date： 2016.11.7 - 2016.11.9
Language：English Presentation type：Oral presentation (general)
Venue： Fuzhou City, Fujian Province, China
-
Reliability and Availability Measures for Internet of Things Consumer World Perspectives International conference
Thi Thi Zin, Pyke Tin, Hiromitsu Hama
The 5th 2016 IEEE Global Conf. on Consumer Electronics (GCCE2016) (Kyoto, Japan) IEEE Consumer Electronics Society
Event date： 2016.10.11 - 2016.10.14
Language：English Presentation type：Oral presentation (general)
Venue：Kyoto, Japan
-
Shape Descriptor for Binary Image Retrieval International conference
Moe Zet Pwint, Thi Thi Zin, Mitsuhiro Yokota, Mie Mie Tin
The 5th 2016 IEEE Global Conf. on Consumer Electronics (GCCE2016) (Kyoto, Japan) IEEE Consumer Electronics Society
Event date： 2016.10.11 - 2016.10.14
Language：English Presentation type：Oral presentation (general)
Venue：Kyoto, Japan
-
User-Intent Visual Information Ranking System International conference
Swe Nwe Nwe Htun, Thi Thi Zin, Mitsuhiro Yokota, Khin Mo Mo Tun
The 5th 2016 IEEE Global Conf. on Consumer Electronics (GCCE2016) (Kyoto, Japan) IEEE Consumer Electronics Society
Event date： 2016.10.11 - 2016.10.14
Language：English Presentation type：Oral presentation (general)
Venue：Kyoto, Japan
-
監視カメラ映像から人物領域抽出を行うための背景差分法の検討
椎屋 和久、神達 翼、Thi Thi Zin
（第69回）電気・情報関係学会九州支部連合大会 (宮崎大学、宮崎市、日本) 電気・情報関係学会九州支部連合大会委員会
Event date： 2016.9.29 - 2016.9.30
Language：Japanese Presentation type：Oral presentation (general)
Venue：宮崎大学、宮崎市、日本
-
画像類似度を用いたランキング手法における特徴量の検討
児嶋 賢也、椎屋 和久、Thi Thi Zin
（第69回）電気・情報関係学会九州支部連合大会 (宮崎大学、宮崎市、日本) 電気・情報関係学会九州支部連合大会委員会
Event date： 2016.9.29 - 2016.9.30
Language：Japanese Presentation type：Oral presentation (general)
Venue：宮崎大学、宮崎市、日本
-
前後2台のカメラを用いたドライバー行動認識における要素技術開発
鈴木 隆哉, Thi Thi Zin
（第69回）電気・情報関係学会九州支部連合大会 (宮崎大学、宮崎市、日本) 電気・情報関係学会九州支部連合大会委員会
Event date： 2016.9.29 - 2016.9.30
Language：Japanese Presentation type：Oral presentation (general)
Venue：宮崎大学、宮崎市、日本
-
The Identification of Dairy Cows Using Image Processing Techniques International conference
Thi Thi Zin, S. Sakurai, K. Sumi, I. Kobayashi, H. Hama
Eleventh International Conference on Innovative Computing Information and Control (ICICIC2016) (Harbin, China) ICIC International, others
Event date： 2016.8.15 - 2016.8.17
Language：English Presentation type：Oral presentation (general)
Venue：Harbin, China
-
Block Base Approach for Key Frame Extraction on Large Video Sequences International conference
Mie Mie Tin, Nyein Nyein Myo, Mie Mie Khin, Thi Thi Zin
Eleventh International Conference on Innovative Computing Information and Control (ICICIC2016) (Harbin, China) ICIC International, others
Event date： 2016.8.15 - 2016.8.17
Language：English Presentation type：Oral presentation (general)
Venue：Harbin, China
-
Markov Chain based Query Classification for User Intent Image Search Engines International conference
Thi Thi Zin, Pyke Tin, Hiromitsu Hama
Eleventh International Conference on Innovative Computing Information and Control (ICICIC2016) (Harbin, China) ICIC International, others
Event date： 2016.8.15 - 2016.8.17
Language：English Presentation type：Oral presentation (general)
Venue：Harbin, China
-
Action Recognition System with the Microsoft KinectV2 using a Hidden Markov Model International conference
Masato Fujino, Thi Thi Zin
The Third Intl. Conf. on Computing Measurement Control and Sensor Network (CMCSN-2016) (Matsue, Shimane, Japan) Waseda University, Fujian University of Technology, others
Event date： 2016.5.20 - 2016.5.22
Language：English Presentation type：Oral presentation (general)
Venue：Matsue, Shimane, Japan
-
Estrus Detection for Dairy Cow Using a Laser Range Sensor International conference
Thi Thi Zin, H. Kai, K. Sumi, I. Kobayashi, H. Hama
The Third Intl. Conf. on Computing Measurement Control and Sensor Network (CMCSN-2016) (Matsue, Shimane, Japan) Waseda University, Fujian University of Technology, others
Event date： 2016.5.20 - 2016.5.22
Language：English Presentation type：Oral presentation (general)
Venue：Matsue, Shimane, Japan
-
A General Video Surveillance Framework for Cow Behavior Analysis International conference
Thi Thi Zin, I. Kobayashi, Pyke Tin, H. Hama
The Third Intl. Conf. on Computing Measurement Control and Sensor Network (CMCSN-2016) (Matsue, Shimane, Japan) Waseda University, Fujian University of Technology, others
Event date： 2016.5.20 - 2016.5.22
Language：English Presentation type：Oral presentation (general)
Venue：Matsue, Shimane, Japan
-
ドライバーの携帯電話使用検知および行動認識に関する研究
鈴木隆哉, Thi Thi Zin
知覚情報/次世代産業システム合同研究会 (新潟大学、新潟、日本) 電気学会
Event date： 2016.3.28 - 2016.3.29
Language：Japanese Presentation type：Oral presentation (general)
Venue：新潟大学、新潟、日本
-
Visual analysis framework for two-person interaction International conference
Thi Thi Zin, J. Kurohane
The 4th IEEE Global Conf. on Consumer Electronics (GCCE 2015) (Osaka, Japan) IEEE Consumer Electronics Society
Event date： 2015.10.27 - 2015.10.30
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan
-
A novel method for product brand ranking in consumer networks International conference
Thi Thi Zin, Pyke Tin, H. Hama
The 4th IEEE Global Conf. on Consumer Electronics (GCCE 2015) (Osaka, Japan) IEEE Consumer Society
Event date： 2015.10.27 - 2015.10.30
Language：English Presentation type：Oral presentation (general)
Venue：Osaka, Japan
-
A color constancy model for non-uniform illumination based on correlation matrix International conference
T. Toriu, M. Hironaga, H. Kamada, Thi Thi Zin
The Tenth International Multi-Conference on Computing in the Global Information Technology
Event date： 2015.10.11 - 2015.10.16
Language：English Presentation type：Oral presentation (general)
-
人物の移動軌跡抽出のための要素技術開発
鈴木隆哉, Thi Thi Zin
平成27年度(第68回) 電気・情報関係学会九州支部連合大会 (福岡大学、日本) 電気・情報関係学会九州支部連合大会
Event date： 2015.9.26 - 2015.9.27
Language：Japanese Presentation type：Oral presentation (general)
Venue：福岡大学、日本
-
コンテンツベース検索のための画像類似度を用いたランキング結果の改善に関する研究
児嶋 賢也、椎屋 和久、Thi Thi Zin
平成27年度(第68回) 電気・情報関係学会九州支部連合大会 (福岡大学、日本) 電気・情報関係学会九州支部連合大会
Event date： 2015.9.26 - 2015.9.27
Language：Japanese Presentation type：Oral presentation (general)
Venue：福岡大学、日本
-
A novel research topic ranking system in academic networks International conference
Thi Thi Zin, Pyke Tin, H. Hama
The 9th International Conference on Genetic and Evolutionary Computing (ICGEC)
Event date： 2015.8.26 - 2015.8.28
Language：English Presentation type：Oral presentation (general)
-
Cow identification by using shape information of pointed pattern International conference
K. Sumi, I. Kobayashi, Thi Thi Zin
The 9th Intl. Conf. on Genetic and Evolutionary Computing (ICGEC2015)
Event date： 2015.8.26 - 2015.8.27
Language：English Presentation type：Oral presentation (general)
-
Framework construction of person violence detection in between two parties
Junpei Kurohane, Thi Thi Zin
Electronics, Information and Communication Engineer' General Conference
Event date： 2015.3.10 - 2015.3.13
Language：Japanese Presentation type：Poster presentation
-
距離画像を用いた人の行動認識に関する研究
藤野 真登，ティティ ズイン
パーティクルフィルタ研究会 (宮崎大学、宮崎市) パーティクルフィルタ研究会
Event date： 2015.2.21
Language：English Presentation type：Oral presentation (general)
Venue：宮崎大学、宮崎市