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Engineering educational research section Information and Communication Technology Program |
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THI THI ZIN
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Degree 【 display / non-display 】
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Doctor of Engineering ( 2007.3 Osaka City University )
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Master of Engineering ( 2004.3 Osaka City University )
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Master of Information Science ( 1999.5 University of Computer Studies, Yangon (UCSY) )
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B.Sc (Hons) (Mathematics) ( 1995.5 University of Yangon (UY) )
Research Interests 【 display / non-display 】
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Image Processing and Its Application
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工場での作業の見える化
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高度な画像処理技術やAI技術を活用した 研究開発
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24-hour monitoring system for the elderly to support independent living
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ICT Farm Monitoring System
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Perceptual information processing
Research Areas 【 display / non-display 】
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Informatics / Perceptual information processing / Image Processing
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Informatics / Database
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Life Science / Animal production science
Papers 【 display / non-display 】
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Hybrid Embedded Feature Matching for Robust Dairy Cow Identification Using 3D Point Cloud Reviewed International journal
Pyae Phyo Kyaw, Pyke Tin, M. Aikawa, I. Kobayashi, Thi Thi Zin
Institute of Electrical and Electronics Engineers Inc., Conference Proceedings (ICCE-Taiwan 2026) 2026.7
Authorship：Last author, Corresponding author Language：English Publishing type：Research paper (international conference proceedings)
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Placement-Free Multi-Camera Monitoring Using Skeletal and Spatial Information Reviewed International coauthorship International journal
Remon Nakashima, Thi Thi Zin, Wan-Jung Chang, Shinji Watanabe
Institute of Electrical and Electronics Engineers Inc., Conference Proceedings (ICCE-Taiwan 2026) 2026.7
Authorship：Corresponding author Language：English Publishing type：Research paper (international conference proceedings)
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A Video-Based Framework for Non-Contact Neonatal Movement Analysis in Clinical Environments Reviewed International journal
Hiroki Matsumoto, Remon Nakashima, Thi Thi Zin, Yuki Kodama
Institute of Electrical and Electronics Engineers Inc., Conference Proceedings (ICCE-Taiwan 2026) 2026.7
Authorship：Corresponding author Language：English Publishing type：Research paper (international conference proceedings)
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Non-contact Monitoring of Dystocia in Dairy Cows Using Keypoint Detection and Semantic Segmentation Reviewed International journal
T. Murayama, Thi Thi Zin, I. Kobayashi, M. Aikawa
The 2026 IEEE International Conference on Consumer Technology – Pacific (ICCT-Pacific 2026) 2026.3
Authorship：Corresponding author Language：English Publishing type：Research paper (international conference proceedings) Publisher：IEEE
In the dairy industry, labor shortages and the economic losses caused by calving accidents are significant issues. To address these problems, we propose a non-contact monitoring system using 360-degree cameras and deep learning techniques. This study focuses on constructing an automated workflow that detects cows, estimates their poses (standing or lying), and tracks individuals without attaching sensors to the animals. We employed YOLO11 for cow detection and keypoint extraction, and compared three models for pose estimation: Multilayer Perceptron (MLP), Gated Recurrent Unit (GRU), and Semantic Segmentation (Deeplabv3+). The experimental results showed that YOLO11 achieved a high detection accuracy (mAP@0.50: 99.47%) for bounding boxes. For pose estimation, the semantic segmentation approach with a ResNet101 backbone achieved the highest accuracy of 85.1%, outperforming keypoint-based methods. These results demonstrate the potential of the proposed system for basic behavioral monitoring in calving barns.
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A Study on Supporting Neurocognitive Disorder Assessment for Deaf Individuals Using a Sign Language Recognition System Reviewed International journal
N. Shibahara, Thi Thi Zin, S. Ito, N. Takahashi, N. Takemoto
The 2026 IEEE International Conference on Consumer Technology – Pacific (ICCT-Pacific 2026) 2026.3
Authorship：Corresponding author Language：English Publishing type：Research paper (international conference proceedings) Publisher：IEEE
The Mini Mental State Examination (MMSE) is widely used for screening Neurocognitive Disorder (NCD); however, ensuring diagnostic accuracy for Deaf individuals remains a challenge due to factors such as the potential subjectivity and translation errors introduced by sign language interpreters. To address this issue, this study proposes an automated MMSE scoring system employing Japanese Sign Language (JSL) recognition based on skeletal keypoints. The proposed method utilizes MediaPipe Pose and Hands to extract feature points from examination videos and employs a Long Short-Term Memory (LSTM) model to classify sign language responses. Evaluation results using 5-fold cross-validation on a dataset of Deaf individuals demonstrated a high average classification accuracy of 92.75%. Furthermore, the system successfully performed automated scoring compliant with the MMSE protocol. These results indicate that the proposed system can enable objective cognitive assessment without interpreter intervention, thereby contributing to more accurate diagnoses for Deaf individuals.
Books 【 display / non-display 】
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Lecture Notes in Electrical Engineering 1322 Reviewed International journal
（ Role： Joint author）
2025.2 （ ISBN:978-981-96-1534-6 ）
Total pages：412 Language：English Book type：Scholarly book
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Lecture Notes in Electrical Engineering (LNEE, volume 1321) Reviewed International journal
（ Role： Joint author）
2025.2 （ ISBN:978-981-96-1530-8 ）
Total pages：528 Language：English Book type：Scholarly book
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Big Data Analysis and Deep Learning Applications: Proceedings of the First International Conference on Big Data Analysis and Deep Learning (Advances in Intelligent Systems and Computing Book 744)
Thi Thi Zin (Editor), Jerry Chun-Wei Lin (Editor) （ Role： Joint editor）
Springer 2018.6
Total pages：Springer Language：English
Other Link： https://www.amazon.com/Data-Analysis-Deep-Learning-Applications-ebook/dp/B07DL46RJX
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Systems and Computing: A New Look into Web Page Ranking Systems
Thi Thi Zin, Pyke Tin, H. Hama, T. Toriu（ Role： Joint author）
Springer International Publishing 2014.10
Language：English Book type：Scholarly book
MISC 【 display / non-display 】
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Bridging Fetal Monitoring and Umbilical Cord Blood Gas Parameter Prediction: A supervised learning approach using fetal heart rate variability
Tunn Cho Lwin, Thi Thi Zin, Pyke Tin, Emi Kino, and Tsuyomu Ikenoue
信学技報 47 - 50 2025.9
Authorship：Corresponding author Language：English Publishing type：Rapid communication, short report, research note, etc. (scientific journal) Publisher：一般社団法人 電子情報通信学会
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画像処理を用いた牛の摂食検知に関する研究
石川 太一、相川 勝、小林 郁雄、THI THI ZIN
信学技報 ( 125 ) 41 - 46 2025.8
Authorship：Last author, Corresponding author Language：English Publishing type：Rapid communication, short report, research note, etc. (scientific journal) Publisher：一般社団法人 電子情報通信学会
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Preface International coauthorship
Pan J.S., Thi Thi Zin, Sung T.W., Lin J.C.W.
Lecture Notes in Electrical Engineering 1322 LNEE v - vii 2025
Authorship：Corresponding author Language：English Publishing type：Rapid communication, short report, research note, etc. (scientific journal) Publisher：Lecture Notes in Electrical Engineering
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A study on Depth Camera-Based Estimation of Elderly Patient Actions
Remon NAKASHIMA, Thi Thi Zin, Kazuhiro KONDO and Shinji Watanabe
37 46 - 52 2024.12
Authorship：Corresponding author Language：Japanese Publishing type：Research paper, summary (national, other academic conference) Publisher：Biomedical Fuzzy Systems Association
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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
Proceedings of the 35th Annual Conference of Biomedical Fuzzy Systems Association (BMFSA2022) 2022.12
Authorship：Corresponding author Language：Japanese Publishing type：Research paper, summary (national, other academic conference) Publisher：Biomedical Fuzzy Systems Association
Presentations 【 display / non-display 】
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A Study on Supporting Neurocognitive Disorder Assessment for Deaf Individuals Using a Sign Language Recognition System International conference
N. Shibahara, Thi Thi Zin, S. Ito, N. Takahashi, N. Takemoto
The 2026 IEEE International Conference on Consumer Technology – Pacific (ICCT-Pacific 2026) 2026.3.30
Event date： 2026.3.28 - 2026.3.30
Language：English Presentation type：Oral presentation (general)
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The Fusion Engine: Gender-Diverse Leadership as the Catalyst for a Sustainable and Intelligent Future Invited International conference
Thi Thi Zin
026 IEEE 2nd International Conference on Consumer Technology – Pacific (ICCT-Pacific 2026) 2026.3.29
Event date： 2026.3.28 - 2026.3.30
Language：English Presentation type：Oral presentation (invited, special)
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Non-contact Monitoring of Dystocia in Dairy Cows Using Keypoint Detection and Semantic Segmentation International conference
T. Murayama, Thi Thi Zin, I. Kobayashi, M. Aikawa
The 2026 IEEE International Conference on Consumer Technology – Pacific (ICCT-Pacific 2026) 2026.3.29
Event date： 2026.3.28 - 2026.3.30
Language：English Presentation type：Oral presentation (general)
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Integrated RGB-Thermographic Vision System for Individual Calf Identification and Health Monitoring International conference
Aung Si Thu Moe, Pyke Tin, Masaru Aikawa, Kazuyuki Honkawa , Thi Thi Zin
The 9th IIEEJ International Conference on Image Electronics and Visual Computing (IEVC-2026) 2026.3.17
Event date： 2026.3.16 - 2026.3.19
Language：English Presentation type：Oral presentation (general)
The increasing demand for sustainable and welfare-oriented livestock farming has accelerated the use of advanced sensing and computer vision technologies. This study presents an integrated RGB-thermographic vision system for individual calf identification and automatic body temperature estimation during feeding at a milk-drinking station. Calves are highly vulnerable to infectious diseases, and traditional health monitoring methods are labor-intensive and inefficient. The proposed system employs a Detectron2 Mask R-CNN with a ResNeXt-101 backbone for calf body region detection and a ResNet-101-based transfer learning model for individual identification. Simultaneously, thermal images are analyzed to detect the calf’s eye and extract temperature data for health evaluation. By combining RGB and thermal modalities, this approach enables contactless, automated, and continuous monitoring, reducing manual intervention and supporting early disease detection in precision livestock farming.
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Top-View Vision System for Individual Cow Identification in Dairy Parlors International conference
Aung Si Thu Moe, Masaru Aikawa, Ikuo Kobayashi, Thi Thi Zin
The 17th International Conference on Genetic and Evolutionary Computing (ICGEC-2025) (Hybrid) 2025.12.19
Event date： 2025.12.18 - 2025.12.19
Language：English Presentation type：Oral presentation (general)
Venue：Hybrid
Awards 【 display / non-display 】
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BEST PAPER AWARD
2025.12 The 17th International Conference on Genetic and Evolutionary Computing (ICGEC-2025) Markovian Digital Twins for Precision Healthcare: A Conceptual Framework
Thi Thi Zin, Tunn Cho Lwin, Pyae Phyo Kyaw, Aung Si Thu Moe, Hiromitsu Hama, Pyke Tin, Tsuyomu Ikenoue
Award type：Award from international society, conference, symposium, etc. Country：China
Abstract. In our current era of swift technological advancement, the concept of digital twins has risen to prominence, serving as a crucial link between tangible objects and their virtual counterparts. This paper introduces the idea of Markovian Digital Twins, integrating the Markov property, a fundamental principle in probability theory, with digital twin technology to address key challenges in precision healthcare. By incorporating Markovian concepts, digital twins can make probabilistic predictions about a system's future states based solely on its current state, enabling proactive decision-making in real-world scenarios. This hybrid approach facilitates optimal decision processes in physical systems, particularly healthcare applications. We illustrate the potential of Markovian Digital Twins by applying them to the study of Autonomic Nervous System functions in humans. The feasibility of the concept is demonstrated through numerical simulations using the real-world SWELL dataset from Radboud University. Although this research is in its early stages, the integration of Markovian principles with digital twin technology offers promising applications in healthcare. This method has the potential to revolutionize how we monitor patients, enhance treatment strategies, and tailor medical care to individual needs. Our research establishes groundwork for a new paradigm in precision healthcare, utilizing the predictive capabilities of Markovian models within the context of digital twins.
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BEST PAPER AWARD
2025.11 The seventh International Conference on. Smart Vehicular Technology, Transportation, Communication and Applications (VTCA2025) Digital Cattle Twins: Revolutionizing Calving Management Through Markovian Prediction Systems
Thi Thi Zin, Tunn Cho Lwin, Aung Si Thu Moe, Pyae Phyo Kyaw, Masaru Aikawa and Pyke Tin
Award type：Award from international society, conference, symposium, etc. Country：China
Abstract: The integration of digital twin technology with livestock management introduces new possibilities in precision livestock farming. Our research proposes the Digital Cattle Twin (DCT) system, a transformative approach to managing cattle calving during the critical periparturient period. This system merges Markovian modeling with real-time visual monitoring to enhance predictive accuracy in calving management. By modeling calving as a sequence of interconnected states within a Markov chain, the DCT predicts progression from early labor to postpartum recovery with high precision. Real-time probability calculations enable early detection of complications and optimal intervention timing. The system integrates diverse data streams, including vaginal temperature sensors for pre-calving temperature drops, AI-based video analysis for behavioral and movement changes, heart rate variability for stress detection, and spatial tracking for calving readiness. A predictive analytics engine processes this multimodal data, achieving high accuracy in detecting risks. The DCT’s adaptive learning architecture refines predictions using both individual and herd-level patterns, enabling a proactive rather than reactive management approach. Beyond calving, this framework illustrates how mathematical modeling and digital twins can redefine livestock management, opening pathways for broader applications in animal health, welfare, and production optimization.
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IEEE GCCE 2025 Excellent Student Paper Award (Outstanding Prize)
2025.9 2025 IEEE 14th Global Conference on Consumer Electronics (GCCE 2025) A Conceptual Framework for Neonatal Motor Activity Monitoring Using Digital Twin Technology and Computer Vision: A Preliminary Study
Remon Nakashima, Thi Thi Zin and Yuki Kodama
Award type：Award from international society, conference, symposium, etc. Country：Japan
Abstract—Continuous non‑contact monitoring of neonatal motor activity in the neonatal intensive care unit (NICU) is crucial for early detection of neurological disorders and for guiding timely clinical interventions. We introduce an infrared‑driven skeleton‑estimation prototype designed for real‑time operation that generates a live virtual “digital twin” of the infant’s posture to support clinician assessment. A deep‑learning pose model was fine‑tuned on a bespoke infrared key‑point dataset, and three motion‑quantification filters were evaluated: raw differencing (Method A), center‑aligned suppression (Method B), and a newly proposed skeleton template‑matching filter (Method C). Tests on a life‑sized neonatal mannequin confirmed centimetric joint‑localization accuracy, reliable detection of 50‑pixel hand displacements, and reduction of simulated camera‑shake artifacts to within five pixels. Building on these results, a follow‑up evaluation on pre‑term neonates showed that Method C suppressed static key‑point noise by 78 % while preserving physiological motion. This combined mannequin and in‑vivo evidence demonstrates the clinical feasibility of our infrared digital‑twin framework and establishes a foundation for automated assessment of pre‑term motor development.
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2025.9 2025 IEEE 14th Global Conference on Consumer Electronics (GCCE 2025) A Conceptual Framework for Neonatal Motor Activity Monitoring Using Digital Twin Technology and Computer Vision: A Preliminary Study
Remon Nakashima, Thi Thi Zin and Yuki Kodama
Award type：Award from international society, conference, symposium, etc. Country：Japan
Abstract—Continuous non‑contact monitoring of neonatal motor activity in the neonatal intensive care unit (NICU) is crucial for early detection of neurological disorders and for guiding timely clinical interventions. We introduce an infrared‑driven skeleton‑estimation prototype designed for real‑time operation that generates a live virtual “digital twin” of the infant’s posture to support clinician assessment. A deep‑learning pose model was fine‑tuned on a bespoke infrared key‑point dataset, and three motion‑quantification filters were evaluated: raw differencing (Method A), center‑aligned suppression (Method B), and a newly proposed skeleton template‑matching filter (Method C). Tests on a life‑sized neonatal mannequin confirmed centimetric joint‑localization accuracy, reliable detection of 50‑pixel hand displacements, and reduction of simulated camera‑shake artifacts to within five pixels. Building on these results, a follow‑up evaluation on pre‑term neonates showed that Method C suppressed static key‑point noise by 78 % while preserving physiological motion. This combined mannequin and in‑vivo evidence demonstrates the clinical feasibility of our infrared digital‑twin framework and establishes a foundation for automated assessment of pre‑term motor development.
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Best Presentation Award
2025.8 The 19th International Conference on Innovative Computing, Information and Control (ICICIC2025) Depth Camera-Based Analysis of Elderly Behavior for Risk Detection Using Skeletal Data
Remon Nakashima, Thi Thi Zin, H. Tamura, S. Watanabe
Award type：Award from international society, conference, symposium, etc. Country：Japan
We present a non-contact, privacy-preserving monitoring system that estimates behavioral risk in elderly-care rooms using depth cameras. First, each video frame is processed to detect individuals and extract 13 skeletal keypoints via a YOLO-based person detector and pose estimator. These keypoints are fed into a two-stage model comprising a graph convolutional network (GCN) and a Transformer encoder, which capture spatial and temporal movement patterns. To contextualize actions, we apply semantic segmentation to identify key regions such as beds and chairs. A rule-based framework then integrates action predictions with spatial overlap between keypoints and environment masks to assign one of three risk levels: Safe, Attention, or Danger. For robustness, we apply temporal smoothing and fuse outputs from two depth cameras. Finally, we design and implement a lightweight graphical user interface (GUI) to visualize risk levels and issue real-time alerts. Experimental results show an overall accuracy of 89.8 % and a hazard-detection accuracy of 74.3 %.
Grant-in-Aid for Scientific Research 【 display / non-display 】
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AIと画像データ解析を活用した牛の摂食行動モニタリングによる持続可能な酪農の実現
Grant number：25K15158 2025.04 - 2028.03
独立行政法人日本学術振興会 科学研究費基金 基盤研究(C)（一般）
Authorship：Principal investigator
畜産は全国農業総生産額の3 割以上を占める重要な産業であるが、不適切な家畜管理による生産性の低下が大きな問題となっている。その主たる原因は飼養形態の変化による1 頭あたり観察時間の短縮であり、飼養頭数の多頭化・農家の高齢化が進む畜産現場において、365 日24 時間にわたり家畜の異常や変化を観察し続けることは困難である。
申請者らは、主に非接触・非侵襲センサ情報のアルゴリズム解析技術に着目し、距離画像とビデオ画像を用いて牛の発情を検知できる独自アルゴリズムの開発に取り組んできた。本研究では、これらの技術を応用することで、牛の発情や分娩監視時の異常を自動検知できる省力的な24 時間
家畜管理システムを開発する。 -
Enhanced AI-Driven Image Analysis for Early Mycoplasma Detection in Dairy Calves for innovations in Livestock Health Management
Grant number：25K15232 2025.04 - 2028.03
独立行政法人日本学術振興会 科学研究費基金 基盤研究(C)（一般）
Authorship：Coinvestigator(s)
畜産は全国農業総生産額の3 割以上を占める重要な産業であるが、不適切な家畜管理による生産性の低下が大きな問題となっている。その主たる原因は飼養形態の変化による1 頭あたり観察時間の短縮であり、飼養頭数の多頭化・農家の高齢化が進む畜産現場において、365 日24 時間にわたり家畜の異常や変化を観察し続けることは困難である。
申請者らは、主に非接触・非侵襲センサ情報のアルゴリズム解析技術に着目し、距離画像とビデオ画像を用いて牛の発情を検知できる独自アルゴリズムの開発に取り組んできた。本研究では、これらの技術を応用することで、牛の発情や分娩監視時の異常を自動検知できる省力的な24 時間
家畜管理システムを開発する。 -
牛の分娩監視システムに関する研究
Grant number：18J14542 2018.04 - 2020.03
科学研究費補助金 特別研究員奨励費
須見 公祐、Thi Thi Zin（受入研究者）
Authorship：Coinvestigator(s)
精度や耐久性が不十分な割に高価なウェラブル型センサの装着や、肉体的・精神的に大きな負担を強いられる目視によるカメラ映像のモニタリング等は、大規模化する畜産現場において現実的なコストで利用できるものが極めて少ない。そこで本研究では、監視カメラから得られる映像を用いて非接触型の分娩管理システムを開発することで、農家そして牛、両方の負担を減らすことを目的とする。
本来、牛は牛群と呼ばれるグループで行動を行う。そして、分娩が間近になると分娩室という分娩専用の牛舎に移される。分娩室には2 頭以上を同時に入れるケースも多く、どの牛で分娩が始まったかを識別する必要があることから、個体識別と追跡処理が必要となる。次に、分娩行動の段階を追って検知を行う。抽出する特徴としては、尻尾が上がっているかどうか、牛が立っているか座っているか、落ち着きがなくなり移動量が増加するか、子牛を出産したかどうか、親牛が子牛を舐めているかどうかなど、それぞれの過程で自動的に異常を見つけ通報を行うアルゴリズムの開発を進める。分娩行動が起きたかどうかの判断は、これらのデータから各特徴の重要度（重み）を学習させることによって行う。そして、最終目標として難産など異常行動の検知を行うために事例を蓄積しながら知識ベースを充実させ、異常事態の検知を行い、分娩の各段階を監視して異常事態の検知ならびに通報が可能なシステムの開発を目指す。 -
画像処理技術と非接触センサを用いた牛の発情検知及び分娩監視システムの開発
Grant number：17K08066 2017.04 - 2021.03
科学研究費補助金 基盤研究(C)
Authorship：Principal investigator
畜産は全国農業総生産額の3 割以上を占める重要な産業であるが、不適切な家畜管理による生産性の低下が大きな問題となっている。その主たる原因は飼養形態の変化による1 頭あたり観察時間の短縮であり、飼養頭数の多頭化・農家の高齢化が進む畜産現場において、365 日24 時間にわたり家畜の異常や変化を観察し続けることは困難である。
申請者らは、主に非接触・非侵襲センサ情報のアルゴリズム解析技術に着目し、距離画像とビデオ画像を用いて牛の発情を検知できる独自アルゴリズムの開発に取り組んできた。本研究では、これらの技術を応用することで、牛の発情や分娩監視時の異常を自動検知できる省力的な24 時間
家畜管理システムを開発する。 -
Development of forensic imaging modality for person identification using integration method of feature correspondences between heterogeneous images
Grant number：15K15457 2015.04 - 2018.03
Grant-in-Aid for Scientific Research Grant-in-Aid for challenging Exploratory Research
Authorship：Coinvestigator(s)
Available Technology 【 display / non-display 】
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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
安全・安心のための24時間自動見守り・監視システムの開発に関する研究
工場の作業効率化のための作業グループ検出に関する研究Home Page： 研究者データベース
Related fields where technical consultation is available：ビッグデータからの新しい知見の獲得・発見を体系的に行える数理的道具の開発
牛のモニタリング情報分析システム
高度な画像処理技術とAI活用による身体・精神機能低下患者の行動認識に関する研究
ビデオ画像を利用した新生児運動モニタリングシステムの開発に関する研究
画像処理技術を用いた疾病の特徴を示すエビを検出するシステムMessage：『画像処理を用いて様々な問題を解決すること』を目的として、農学や医学の分野に係わる学際領域の研究を幅広く行っています。多種多様な課題に対して各分野の専門家と協力して、画像処理分野からの貢献を目指して、研究・開発を行っています。