受賞 - ティティズイン
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IEEE GCCE 2022 Excellent Student Paper Awards (Outstanding Prize)
2022年10月 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE2022) Video-Based Automatic Cattle Identification System
Su Larb Mon, Thi Thi Zin, Pyke Tin, I. Kobayashi
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
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(You 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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Best Presentation Award
2022年9月 The 16th International Conference on Innovative Computing, Information and Control (ICICIC2022) Comparative Study on Color Spaces, Distance Measures and Pretrained Deep Neural Networks for Cow Recognition
Cho Cho Mar, Thi Thi Zin, Pyke Tin, I. Kobayashi, K. Honkawa, Y. Horii
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
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Best Presentation Award
2022年3月 The Fifth International Symposium on Information and Knowledge Management (ISIKM2022) Black Cow Localization and Tracking with YOLOv5 and Deep SORT
Cho Cho Aye, Thi Thi Zin, I. Kobayashi
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
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IEEE LifeTech 2022 WIE Excellent Paper Award
2022年3月 IEEE 4th Global Conference on Life Sciences and Technologies(LifeTech2022) A Hybrid Approach: Image Processing Techniques and Deep Learning Method for Cow Detection and Tracking System
Cho Cho Mar, Thi Thi Zin, I. Kobayashi, Y. Horii
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
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.
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IEEE GCCE2021 Excellent Paper Award Gold Prize
2021年10月 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE2021) Evaluation of the Severity of Tremor Based on Each Signal Acquired from the Displacement of the Hand Movements
T. Hayashida, Thi Thi Zin, K. Sakai, H. Mochizuki
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
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%.
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Best Presentation Award
2021年9月 15th International Conference on Innovative Computing, Information and Control (ICICIC2021) Application of Methods in Sequential Analysis to Dairy Cow Calving Events
Thi Thi Zin, K. Sumi, Pann Thinzar Seint, Pyke Tin, I. Kobayashi
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
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IEEE LifeTech 2021 WIE Paper Award
2021年3月 IEEE 3rd Global Conference on Life Sciences and Technologies(LifeTech2021) Automatic Detection of Mounting Behavior in Cattle using Semantic Segmentation and Classification
Su Myat Noe, Thi Thi Zin, Ikuo Kobayashi, Pyke Tin
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
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IEEE LifeTech 2020 WIE Paper Award
2020年3月 IEEE 2nd Global Conference on Life Sciences and Technologies(LifeTech2020) Human Action Analysis Using Virtual Grounding Point and Motion History
Swe Nwe Nwe Htun, Thi Thi Zin, Hiromitsu Hama
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
In this paper, we propose an approach to human action analysis for home care monitoring system in the aspect of image processing and life science technologies. We introduce a new concept of a virtual grounding point representing the position of a target person as an innovated feature for action analysis. Specifically, in developing action analysis, the background subtraction is firstly conducted by applying the Mixture of Gaussian and low rank subspace learning. After that, the graph cut is embedded to enhance the foregrounds in order to detect both of moving and motionless object. Secondly, the virtual grounding point is calculated by using the centroid of silhouette image. Finally, motion of the person is estimated by using timed motion history image in order to improve the accuracy of action analysis. A series of the experiments are conducted to confirm the effectiveness of the proposed method.
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IEEE GCCE 2019 Excellent Student Paper Award (Silver Prize)
2019年10月 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE2019) Emotion Analysis of Twitter Users on Natural Disasters
Nann Hwan Khun,Thi Thi Zin, Mitsuhiro Yokota, Hninn Aye Thant
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
In this information era, people usually express their views and emotions on a wide range of topics through social networking sites and so the role of emotion analysis in social media has been the subject of considerable research. The idea behind this research is that the emotions people express in their status updates can tell us something about how their emotions fluctuate day-to-day due to natural disasters. In this paper, we targeted for emotion analysis of Twitter users on natural disasters. By identifying these emotions, we can help first responders for better managing the situations such as mental health of survived victims. Our experiment is based on California Camp Fire that is happened in 2018 November.
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Best Student Paper Award of The 2018 IAENG International Conference on Imaging Engineering
2018年9月 IMECS 2018 (Intlernational MultiConference of Engineers and Computer Scientists 2018) A Study on Disease Diagnosis by Tremor Analysis
三井 優一、 石井 信之、 望月 仁志、 Thi Thi Zin
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:ホンコン(香港)特別行政区
Tremor is a symptom in which a part of the body (hands, feet, head, etc.) trembles involuntarily. Essential tremor and cerebellar disorders are examples of diseases with tremor, but it is sometime difficult to accurately diagnose these diseases by only physical examination, and there is no indicator to quantitatively evaluate the tremor. In this study, we analyzed the Finger-Nose-Finger (FNF) test, which is a physical examination for detecting patients’ tremor, using image processing technology, and proposed an index to discriminate between essential tremor and cerebellar disorders.
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Certificate of Merit for The 2018 IAENG International Conference on Imaging Engineering
2018年9月 IMECS 2018 (Intlernational MultiConference of Engineers and Computer Scientists 2018) Image Technology based Cow Identification System Using Deep Learning
Thi Thi Zin, Cho Nilar Phyo, Pyke Tin, Hiromitsu Hama, Ikuo Kobayashi
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:ホンコン(香港)特別行政区
Today worldwide trending in precision dairy farming is becoming more focus on an individual cow welfare and health rather than group management by using modern technologies including image processing techniques. In such cases, individual cow identification is one of the fundamental ingredients for the success of modern dairy farming. Thus, in this paper we shall explore and examine how image processing technologies can be utilized in analyzing and identifying individual cows along with deep learning techniques. This system is mainly focus on the identification of individual cow based on the black and white pattern of the cow’s body. In our system, firstly we detect the cow’s body which have been placed on the Rotary Milking Parlour by using the inter-frame differencing and horizontal histogram based approach. Then, we crop the cow’s body region by using the predefined distance value. Finally, the cropped images are used as input data for training the deep convolutional neural network for the identification of individual cow’s pattern. The experiments are performed on the self-collected cow video dataset which have been taken at the large-scale ranch in Oita Prefecture, Japan. According the experimental result, our system got the accuracy of 86.8% for automatic cropping of cow’s body region and 97.01% for cow’s pattern identification. The result shows that our system can automatically recognize each individual cow’s pattern very well.
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Certificate of Merit (Student) for The 2018 IAENG International Conference on Imaging Engineering
2018年9月 IMECS 2018 (Intlernational MultiConference of Engineers and Computer Scientists 2018) Image Technology based Students' Feedbacks Analyzing System using Deep Learning
Cho Nilar Phyo, Thi Thi Zin, Hiroshi Kamada, Takashi Toriu
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:ホンコン(香港)特別行政区
In these days, the integration of technology in teaching-learning process has become a central role in order to redesign a quality education system especially for the development of interactive education. In this concern, technology based analysis on the interaction between students and teacher and the feedback of the students play key roles. Thus, in this paper, we proposed the automatic students’ feedbacks analyzing system for the purpose of speeding up the communication between students and teacher in the classroom by using the image processing and deep learning technology. In the proposed system, the students can use the five kind of color cards for answering the questions or for describing their feedbacks. Then the automatic students’ feedback analyzing system will analyze the color cards objects by using the camera and describe the analyzed result to the teacher. In this way, the interaction between students and teacher can be faster and can give a lot of benefit for the education system. In order to implement this system, firstly, the color objects segmentation is performed over the input image using the predefined color thresholds. Then, the noise objects are removed by using the predefined maximum size and minimum size thresholds. Finally, the Deep Convolutional Neural Network (DCNN) is applied in order to classify the five color cards objects and non-card color objects. The experiments are performed on the image that have been taken in the large classroom under the different illumination condition. According to the experimental results, the proposed system can robustly analyze the color cards objects with the accuracy of 97.02% on the training data and 94.38% for the testing data. The proposed system can give the ubiquitous (anytime, anywhere) analyzing of the students’ feedback in the classroom.
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Certificate of Merit for The 2018 IAENG International Conference on Imaging Engineering
2018年9月 IMECS 2018 (Intlernational MultiConference of Engineers and Computer Scientists 2018) Markov Chain Techniques for Cow Behavior Analysis in Video-based Monitoring System
Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Hiromitsu Hama
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:ホンコン(香港)特別行政区
In this paper we shall explore and examine how Markov Chain techniques of stochastic processes can be utilized to analyze cow behaviors in video-based monitoring systems. In this aspect due to shortage of human experts for monitoring the video-based monitoring system has become a powerful technique to replace for human experts. Moreover the image processing methods will play major roles in analyzing visual behaviors such as cow identification, estrus detection, prediction of calving time and body condition scoring etc. Since cow behaviors are changing with respect to times and related to immediate past, Markov Chain models will be very useful enforce the image processing techniques. Although there has been a tremendous amount of methods for detecting estrus, still it needs to improve for achieving a more accurate and practical. Thus in this paper, cow behaviors are to be analyzed by using Gamma Type Markov Chain Models. In particular, image processing methods will be performed to detect cow activities such as standing, lying and walking in association with time, space and frequencies. Then collected data are to be modeled by using Markov Chain for decision making process. As an illustration, we provide some simulation results based on gamma random number generated data.
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Best Student Paper Award
2018年8月 SOLI 2018 (The 2018 IEEE Intl. Conf. on Service Operations and Logistics, and Informatics) Ranking of Influential Users Based on User-Tweet Bipartite Graph
Radia EL BACH, Thi Thi Zin
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:シンガポール共和国
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.
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電気学会産業応用部門研究会 部門優秀論文発表賞
2018年3月 一般社団法人 電気学会 産業応用部門 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
受賞区分:国内学会・会議・シンポジウム等の賞 受賞国:日本国
Generally speaking, individual identification of cows is done in many cases with ear tags or RFID (Radio Frequence Identifier). In this way, we attach it directly to the body of a cow, but they dislike being attached to cows and feel stresses, so some cow's milk and meat quality falls. In this paper, we aimed to develop a system that automatically detects individual identification by the image processing technology with the pattern of the back of a cow taken from the camera.
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宮崎大学女性研究者奨励賞
2018年2月 宮崎大学 女性研究者奨励賞(地域・国際貢献部門)
Thi Thi Zin
受賞国:日本国
以下の地域貢献並びに国際貢献を積極的に行っています。
地域貢献:
・高齢者見守りシステムの構築
・ICT技術を活用した牛の監視・見守りシステムの構築
国際貢献:
・宮崎大学とミャンマー国科学技術省との間で学術交流包括協定(MOU)を締結支援
・工学研究科修士課程DDP(ダブルデグリープログラム)の推進
・JST日本・アジア青少年サイエンス交流計画を活用した若手研修生の受入
・宮崎大学ヤンゴンオフィス開所や産官学交流会開催の支援 -
Excellent Paper Award
2017年11月 The 11th International Conference on Genetic and Evolutionary Computing (ICGEC2017) Markov Queuing Theory Approach to Internet of Things Reliability
Thi Thi Zin, Pyke Tin, Hiromitsu Hama
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:台湾
In today world a new buzzword Internet of Things has been on the news nearly every day. Some researchers are even using Internet of Every Things. Its potentialities and applicability are now on the cutting edge technology. Also, all most all of business, health care, academic institutions are in one way or another, having to deal with the Internet of Things. So the Internet of Things reliability becomes an important factor. In this paper we proposed a Markov Queuing approach to analyze the Internet of Thing reliability. Since queuing theory investigates the delay and availability of functioning things and Markov concepts take the dependency of Things in the Internet, the combination of these two concepts will make the problem clear and soluble. For illustration, we present some experimental results.
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1st Prize IEEE GCCE 2017 Student Paper Award
2017年10月 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE2017) Automatic Evaluation of Cow's Body-Condition-Score Using 3D Camera
Sosuke Imamura, Thi Thi Zin, Ikuo Kobayashi, Yoichiro Horii
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
Body Condition Scoring (BCS) is a method of evaluating fatness or thinness in cows, and it is important to manage productivity of the cows. However, it is not easy to measure BCS by observing animals because it consumes much time and costs, especially in the large-scale farming. Therefore, almost farmers are not conducting regular evaluation of BCS. In this paper, we propose the noninvasive method for automated evaluation of cow's BCS by using 3D camera and image processing technology.
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Best Paper Award
2016年11月 The 10th International Conference on Genetic and Evolutionary Computing (ICGEC2016) Deep Learning Model for Integration of Clustering with Ranking in Social Networks
Thi Thi Zin, Pyke Tin, Hiromitsu Hama
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:中華人民共和国
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IEEE GCCE2016 Best Paper Award
2016年10月 The 5th IEEE Global Conference on Consumer Electronics(GCCE2016) User-Intent Visual Information Ranking System
Swe Nwe Nwe Htun, Thi Thi Zin, Mitsuhiro Yokota, Khin Mo Mo Tun
受賞区分:国際学会・会議・シンポジウム等の賞 受賞国:日本国
平成28年10月11日~14日,京都で開催されたThe 5th IEEE Global Conference on Consumer Electronics(GCCE2016)において,宮崎大学工学研究科電気電子工学専攻2年のSwe Nwe New Tun氏が“User-Intent Visual Information Ranking System”と題した論文を発表しました.
本研究では,ユーザーの意図を反映するウェブ画像検索システムを目的としている。システムから返されたイメージとユーザーの意図との間の関連性を向上させるために、ソーシャルネットワークの共有パターンを組み合わせている。このことにより、Web画像検索のためのアプローチと再ランキングシステムをランク付けするユーザー指向の視覚情報システムを提案している。画像類似度のためにマルコフ定常特徴、テクスチャー特徴、色特徴を用いて良好な結果を得ている。以上より、本研究内容が評価され“Best Paper Award”を受賞しました。