Awards - THI THI ZIN
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Best Presentation Award
2025.4 2025 10th International Conference on Multimedia and Image Processing (ICMIP 2025) Machine learning-based prediction of cattle body condition score using 3D point cloud surface features
Pyae Phyo Kyaw, Thi Thi Zin, Pyke Tin, M. Aikawa, I. Kobayashi
Award type：Award from international society, conference, symposium, etc. Country：Japan
Body Condition Score (BCS) of dairy cattle is a crucial indicator of their health, productivity, and reproductive performance throughout the production cycle. Recent advancements in computer vision techniques has led to the development of automated BCS prediction systems. This paper proposes a BCS prediction system that leverages 3D point cloud surface features to enhance accuracy and reliability. Depth images are captured from a top-view perspective and processed using a hybrid depth image detection model to extract the cattle’s back surface region. The extracted depth data is converted into point cloud data, from which various surface features are analyzed, including normal vectors, curvature, point density, and surface shape characteristics (planarity, linearity, and sphericity). Additionally, Fast Point Feature Histograms (FPFH), triangle mesh area, and convex hull area are extracted and evaluated using three optimized machine learning models: Random Forest (RF), K-Nearest Neighbors (KNN), and Gradient Boosting (GB). Model performance is assessed using different tolerance levels and error metrics, including Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). Among the models, Random Forest demonstrates the highest performance, achieving accuracy rates of 51.36%, 86.21%, and 97.83% at 0, 0.25, and 0.5 tolerance levels, respectively, with an MAE of 0.161 and MAPE of 5.08%. This approach enhances the precision of BCS estimation, offering a more reliable and automated solution for dairy cattle monitoring and health management.
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Best Presentation Award
2025.4 2025 10th International Conference on Multimedia and Image Processing (ICMIP 2025) Minimizing Resource Usage for Real-Time Network Camera Tracking of Black Cows
Aung Si Thu Moe, Thi Thi Zin, Pyke Tin, M. Aikawa, I. Kobayashi
Award type：Award from international society, conference, symposium, etc. Country：Japan
Livestock plays a crucial role in the farming industry to meet consumer demand. A livestock monitoring system helps track animal health while reducing labor requirements. Most livestock farms are small, family-owned operations. This study proposes a real-time black cow detection and tracking system using network cameras in memory and disk constrained environments. We employ the Detectron2 Mask R-CNN ResNeXt-101 model for black cow region detection and the ByteTrack algorithm for tracking. ByteTrack tracks multiple objects by associating each detection box. Unlike other deep learning tracking algorithms that use multiple features such as texture, color, shape, and size. ByteTrack effectively reduces tracking ID errors and ID switches. Detecting and tracking black cows in real-time is challenging due to their uniform color and similar sizes. To optimize performance on low-specification machines, we apply ONNX (Open Neural Network Exchange) to the Detectron2 detection model for optimization and quantization. The system processes input images from network cameras, enhances color during preprocessing, and detects and tracks black cows efficiently. Our system achieves 95.97% mAP@0.75 detection accuracy and 97.16 % in daytime video and 94.83 % in nighttime accuracy of tracking are effectively tracks individual black cows, minimizing duplicate IDs and improving tracking after missed detections or occlusions. The system is designed to operate on machines with minimal hardware requirements.
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2024.12 SOFT九州支部【学会名】第26回日本知能情報ファジィ学会九州支部学術講演会 マハラノビス距離を用いた胎児心拍変動の定量的評価とpH分類
Tunn Cho Lwin, Thi Thi Zin, Pyke Tin, 紀 愛美, 池ノ上 克
Award type：Award from Japanese society, conference, symposium, etc. Country：Japan
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2024.12 SOFT九州支部【学会名】第26回日本知能情報ファジィ学会九州支部学術講演会 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
Award type：Award from Japanese society, conference, symposium, etc. Country：Japan
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Best Presentation Award
2024.9 18th International Conference on Innovative Computing, Information and Control (ICICIC2024) Integrating Entropy Measures of Fetal Heart Rate Variability with Digital Twin Technology to Enhance Fetal Monitoring
Tunn Cho Lwin, Thi Thi Zin, Pyae Phyo Kyaw, Pyke Tin, E. Kino and T. Ikenoue
Award type：Award from international society, conference, symposium, etc. Country：China
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Best Paper Award
2024.9 6TH IEEE MASS WORKSHOP ON SMART LIVING WITH IOT, CLOUD, AND EDGE COMPUTING ( COLOCATED WITH IEEE MASS 2024) Analyzing Parameter Patterns in YOLOv5-based Elderly Person Detection Across Variations of Data
Ye Htet, Thi Thi Zin, Pyke Tin, H. Tamura, K. Kondo, S. Watanabe, E. Chosa
Award type：Award from international society, conference, symposium, etc.
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Best Paper Award
2024.8 The 16th International Conference on Genetic and Evolutionary Computing (ICGEC-2024) Cattle Lameness Detection Using Leg Region Keypoints from a Single RGB Camera
Bo Bo Myint, Thi Thi Zin, M. Aikawa, I. Kobayashi and Pyke Tin
Award type：Award from international society, conference, symposium, etc. Country：Japan
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Best Paper Award
2024.8 The 16th International Conference on Genetic and Evolutionary Computing (ICGEC-2024) Utilizing Behavioral Features for Predicting Calving Time
Wai Hnin Eaindrar Mg, Pyke Tin, M. Aikawa, I. Kobayashi, Y. Horii, K. Honkawa, Thi Thi Zin
Award type：Award from international society, conference, symposium, etc. Country：Japan
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Best Paper Award
2024.8 The 16th International Conference on Genetic and Evolutionary Computing (ICGEC-2024) Applying Digital Restoration Techniques in Preservation of Ancient Murals using DiffusionBased Inpainting
Khant Khant Win Tint, Mie Mie Tin, Thi Thi Zin and Pyke Tin
Award type：Award from international society, conference, symposium, etc. Country：Japan
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Best Paper Award
2024.8 The 16th International Conference on Genetic and Evolutionary Computing (ICGEC-2024) Cattle Lameness Classification Using Cattle Back Depth Information
San Chain Tun, Pyke Tin, M. Aikawa, I. Kobayashi and Thi Thi Zin
Award type：Award from international society, conference, symposium, etc. Country：Japan
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Best Paper Award
2024.8 The 16th International Conference on Genetic and Evolutionary Computing (ICGEC-2024) Identification of Rumination Patterns in Cattle Through Optical Flow Analysis and Machine Learning Techniques
T. Ishikawa, Thi Thi Zin, M. Aikawa, I. Kobayashi
Award type：Award from international society, conference, symposium, etc. Country：Japan
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Best Paper Award
2024.8 The 16th International Conference on Genetic and Evolutionary Computing (ICGEC-2024) From Vision to Vocabulary: A Multimodal Approach to Detect and Track Black CAttle Behaviors
Su Myat Noe, Thi Thi Zin, Pyke Tin and I. Kobayashi
Award type：Award from international society, conference, symposium, etc. Country：Japan
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Student paper Award
2024.3 2024 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing Kalman Velocity-based Multi-Stage Classification Approach for Recognizing Black Cow Actions
Cho Cho Aye, Thi Thi Zin, M. Aikawa, I. Kobayashi
Award type：Award from international society, conference, symposium, etc.
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Student paper Award
2024.3 2024 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing Enhancing Precision Agriculture: Innovative Tracking Solutions for Black Cattle Monitoring
Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi
Award type：Award from international society, conference, symposium, etc.
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Best Paper Award
2023.11 The 9th International Conference on Science and Technology (ICST UGM 2023) An Innovative Framework for Cattle Activity Monitoring: Combining AI-Based Markov Chain Model with IoT Devices
Y. Hashimoto, Thi Thi Zin, Pyke Tin, I. Kobayashi and H. Hama
Award type：Award from international society, conference, symposium, etc.
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IEEE GCCE 2022 Excellent Student Paper Awards (Outstanding Prize)
2022.10 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
Award type：Award from international society, conference, symposium, etc. 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(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
2022.9 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
Award type：Award from international society, conference, symposium, etc. Country：Japan
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Best Presentation Award
2022.3 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
Award type：Award from international society, conference, symposium, etc. Country：Japan
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IEEE LifeTech 2022 WIE Excellent Paper Award
2022.3 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
Award type：Award from international society, conference, symposium, etc. 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.
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IEEE GCCE2021 Excellent Paper Award Gold Prize
2021.10
Award type：Award from international society, conference, symposium, etc. Country：Japan