Yuji WATANABE
- Division
- Mathematical and Material Science, Professor
- Academic Degree
- Ph.D. (Engineering)
| Research Field | Intelligent Informatics, Information Security |
|---|---|
| Keywords | Artificial Intelligence, Machine Learning, Security, Biometrics Authentication, Sensor Networks, Programming Education |
| Current Research Topics | (1) Behavior-based Biometrics Authentication on Mobile Device: We develop a behavior-based biometrics authentication system to continuously monitor user operations and behaviors in the background under various circumstances using multiple sensors built into mobile device such as smart phone. (2) Construction of Ambient Sensor Network And Motion Estimation Using Machine Learning: Using an ambient sensor network consisting of sensors installed in clothes, bed, treatment equipment, etc. and mobile devices, we apply machine learning including deep learning to the subject's motion data to estimate the subject's motion and state. (3) Teaching Support Using Machine Learning in Primary Programming Education: In elementary programming classes, we aim to create a programming education support system that accumulates the source code and the operation history of learners, systemizes teaching methods by machine learning, and presents the teaching methods to elementary, junior high and high school teachers. |
| Selected Publications | A Mobile Real-time Identification System of Isomorphic Objects Using YOLO with Attention for Visually Impaired People, 2024 IEEE 13th Global Conference on Consumer Electronics (GCCE), pp.121-122 (2024). (Excellent Student Poster Awards) Proposed Models for Improving Lesion Segmentation in Ischemic Stroke CT Images Based on Hybrid CNN-Transformer Architectures, 2024 IEEE 13th Global Conference on Consumer Electronics (GCCE), pp.975-976 (2024). Real-time Identification System Using YOLO and Isomorphic Object Identification for Visually Impaired People, 2023 IEEE 12th Global Conference on Consumer Electronics (GCCE), pp.757-758 (2023). NP4G: Network Programming for Generalization, IntelliSys 2023: Intelligent Systems and Applications, pp.301-315 (2023). Motion Estimation by Deep Learnings Using Ambient Sensor Network, 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE), pp.398-399 (2022). Tendency Analysis of Python Programming Classes for Junior and Senior High School Students, Procedia Computer Science, Vol.207, pp.4603-4612 (2022). GI-SleepNet: A Highly Versatile Image-Based Sleep Classification Using a Deep Learning Algorithm, Clocks & Sleep, Vol.3, No.4, pp.581-597 (2021). Gait identification and authentication using LSTM based on 3-axis accelerations of smartphone, Procedia Computer Science, Vol.176, pp.3873-3880 (2020). Identification and features selection of elderly people based on accelerations of smartphone, Procedia Computer Science, Vol.159, pp.2629-2638 (2019). Long-term influence of user identification based on touch operation on smart phone, Procedia Computer Science, Vol.112, pp.2529-2536 (2017). Toward an Immunity-based Gait Recognition on Smart Phone: A Study of Feature Selection and Walking State Classification, Procedia Computer Science, Vol.96, pp.1790-1800 (2016). Toward Application of Immunity-based Model to Gait Recognition Using Smart Phone Sensors: A Study of Various Walking States, Procedia Computer Science, Vol.60, pp.1856-1864 (2015). Influence of Holding Smart Phone for Acceleration-based Gait Authentication, Proc. of IEEE 2014 International Conference on Emerging Security Technologies (EST), pp.30-33 (2014). |