Shimizu Akinobu | Tokyo University Of Agriculture And Technology
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概要
関連著者
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Shimizu Akinobu
Tokyo University Of Agriculture And Technology
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Kobatake Hidefumi
Tokyo Univ. Agriculture & Technol. Tokyo Jpn
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Shimizu Akinobu
Tokyo University of Agriculture & Technology
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Kobatake H
Tokyo Univ. Agriculture & Technol. Tokyo Jpn
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Kobatake Hidefumi
Tokyo University of Agriculture and Technology
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Hagihara Y
Tokyo University Of Agriculture & Technology
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Yao Cong
Tokyo University Of Agriculture And Technology
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NAWANO Shigeru
National Cancer Center Hospital East
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Shimizu A
Tokyo University Of Agriculture And Technology
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Shimizu Akinobu
Graduate School Of Base Tokyo University Of Agri. & Tech.
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WADA Takashige
Tokyo University of Agriculture and Technology
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LIPIKORN Rajalida
Tokyo University of Agriculture & Technology
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HAGIHARA Yoshihiro
Tokyo University of Agriculture & Technology
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Huang Linlin
Tokyo University of Agriculture & Technology
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Huang Linlin
Graduate School Of Base Tokyo University Of Agri. & Tech.
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Lipikorn Rajalida
Tokyo University Of Agriculture & Technology
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TAKEO Hideya
Fuji Photo Film Co., Ltd.
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SHIMURA Kazuo
Fuji Photo Film Co., Ltd.
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IMAMURA Takashi
Fuji Film Software Co., Ltd.
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Takeo Hideya
Fuji Photo Film Co. Ltd.
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Imamura Takashi
Fuji Film Software Co. Ltd.
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Shimura Kazuo
Fuji Photo Film Co. Ltd.
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Lipikorn Rajalida
Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology
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SHINOZAKI Kenji
Kyushu Cancer Center
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FURUKAWA Daisuke
Tokyo University of Agriculture and Technology
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NARIHIRA Takuya
Tokyo University of Agriculture and Technology
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NAWANO Shigeru
International University of Health and Welfare
著作論文
- Proposal of Atlas-guided Eigen-organ Method for Location Detection of Multi-Organs in Three Dimensional Medical Images(Joint Session 2)
- A Modified Exoskeleton for 3D Shape Description and Recognition
- LI-7 Face detection based on gradient features and polynomial neural network
- Detection System of Clustered Microcalcifications on CR Mammogram(Biological Engineering)
- Ensemble Learning Based Segmentation of Metastatic Liver Tumours in Contrast-Enhanced Computed Tomography