Shengzhe Jiao, Yihong Zhang, Yuanyuan Wang, Shingo Mabu, Haoyang Xia, Takahiro Hara. Multi-modal Contrastive Learning For Medical Image Classification with Limited Training Data (accepted). Proc. of the 23rd IEEE International Conference on Machine Learning and Applications. 2024
Ryosuke Wakamoto, Shingo Mabu. Effective Feature Extraction from Lung Sounds Using Time-Series Neural Networks. Proc. of the 2024 63rd Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). 2024. 846-851
Ibuki YAMANAKA, Saya NARITA, Shingo MABU, Kunhao YANG, Shoji KIDO. Design of Deep Learning Models for Anatomic and Normal/Abnormal Classification in the Sentences of PET-CT Image Findings. Proc. of JAMIT Annual Meeting 2024. 2024. 284-285
Mikiya MORISAKI, Shingo MABU, Shoji KIDO. Proposal for the Effective Utilization of Voxel Data for the Classification of Diffuse Lung Diseases in Chest CT Images. Proc. of JAMIT Annual Meeting 2024. 2024. 158-159
Minori IWASE, Shingo MABU, Kunhao YANG, Shoji KIDO. Opacity Classification and Anomaly Detection of Diffuse Lung Diseases in Chest CT Using Federated Learning. Proc. of JAMIT Annual Meeting 2024. 2024. 148-149
Shingo Mabu. Landslide Area Detection from Synthetic Aperture Radar (SAR) Images Using Convolutional Neural Networks. Systems, Control and Information. 2021. 65. 2. 39-46
Shingo Mabu. Effective learning methods on a small number of training data. Clinical Imagiology. 2019. 34. 10. 1157-1168
Medical Data Analysis Using Deep Learning -Study on the Utilization of Limited Number of Labeled Data-
(2024)
Fundamentals and Trends of Artificial Intelligence (AI) and University Initiatives
(2023)
AI/Machine Learning Methods for Making Use of Limited Number of Training Data and Its Applications to Medical Data Analysis
(The sixth workshop of Committee for the Creation of AI-based Systems 2022)
Prediction of Physical Activity and Evaluation of Test Item Importance in Chronic Obstructive Pulmonary Disease Using Neural Network
(The 13th Japanese Society of Pulmonary Functional Imaging 2022)
2003 - 2006 Waseda University Graduate School of Information Production and Systems
2001 - 2003 Kyushu University Graduate School of Information Science and Electrical Engineering Department of Electrical and Electronic System Engineering
1997 - 2001 Kyushu University School of Engineering Electrical Engineering and Computer Science
Professional career (3):
Doctor of Engineering (Waseda University)
Master of Engineering (Kyushu University)
学士(工学) (九州大学)
Work history (9):
2020/10 - 現在 Yamaguchi University Graduate School of Sciences and Technology for Innovation Professor
2017/03 - 2020/09 Yamaguchi University Graduate School of Sciences and Technology for Innovation Associate Professor
2016/04 - 2017/03 Yamaguchi University Graduate School of Sciences and Technology for Innovation Assistant Professor
2012/09 - 2016/03 Yamaguchi University Graduate School of Science and Engineering Assistant Professor
2009 - 2012/08 Waseda University Faculty of Science and Engineering
2007 - 2008 Waseda University Graduate School of Information Production and Systems
2006 - 2007 (財)北九州産業学術推進機構 特別研究員
2006 - 2007 Waseda University Research Institute for Science and Engineering Visiting Lecturer
2003 - 2006 日本学術振興会 特別研究員(DC1)
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Committee career (42):
2013/01 - 現在 計測自動制御学会 システム・情報部門 システム工学部会 運営委員
2012 - 現在 Journal of Advanced Computational Intelligence and Intelligent Informatics 編集委員
2023/06 - 2023/11 IEEE SMC Hiroshima Chapter 2023 IEEE 13th International Workshop on Computational Intelligence and Applications (IWCIA2023) Committee Member
2019/01 - IFMIA2019 IFMIA Best Paper Award Analysis of the Effects of Transfer Learning on Opacity Classification of Diffuse Lung Diseases Using Convolutional Neural Network
2018/07 - 山口大学工学部 最優秀授業 ものづくり創成実習II(2017)
2016/12 - IRE-Asia Consortium Best Paper Award Learning Embedding Functions for Instance-based Reinforcement Learning with Matching Networks
2015/01/17 - International Conference on Artificial Life and Robotics Best Paper Award at The 2015 International Conference on Artificial Life and Robotics