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The long-term goal of Dr. Suzuki’s research is to develop and understand computational intelligence that learns, from data and examples, experts’ knowledge and skills in understanding images in order to make smart decisions. To approach his goal, he believes that the development of sophisticated machine-learning and image-analysis techniques, their theoretical backups, and an understanding of experts’ decision-making process and of the human visual system are essential. Areas of his interest include machine/data learning in biomedical imaging, computer-aided detection and diagnosis of lesions in biomedical images, and biomedical image processing and analysis, especially machine learning inspired by the human visual system for image processing and pattern recognition such as image-based machine learning and deep learning, and its applications in biomedicine.
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论文共 456 篇作者统计合作学者相似作者
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Usman Mahmood,Amita Shukla-Dave,Heang-Ping Chan,Karen Drukker, Ravi K Samala,Quan Chen, Daniel Vergara,Hayit Greenspan,Nicholas Petrick,Berkman Sahiner,Zhimin Huo,Ronald M Summers,
BJR artificial intelligenceno. 1 (2024): ubae003-ubae003
2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)pp.1647-1651, (2023)
Srisopitsawat Pavarut,Wongsakorn Preedanan,Itsuo Kumazawa,Kenji Suzuki,Masaki Kobayashi,Hajime Tanaka,Junichiro Ishioka,Yoh Matsuoka, Yasuhisa Fuji
IEEE ACCESS (2023): 146250-146261
2023 45TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY, EMBC (2023): 1-7
2023 ASIA PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE, APSIPA ASCpp.1343-1348, (2023)
IEEE Access (2023): 25702-25712
MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, MICCAI 2023, PT II (2023): 713-722
MEDICAL IMAGING 2023 (2023)
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