Presentations -
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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)
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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)
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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
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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
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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
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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
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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.
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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)
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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)
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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
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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
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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