Contents Science Lab

Nagoya University Graduate School of Informatics
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Akinori Sato

Finished Master in AY2018

Main projects

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Food attractiveness measurements

In this research, we analyze the attractiveness of food images using image analysis, including gaze information to improve the results.

Recent publications

    Gaze-inspired learning for estimating the attractiveness of a food photo
    Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
    Proc. 20th IEEE Int. Symposium on Multimedia (ISM2018), pp.36-43, The Splendor Hotel Taichung (Taichung, Taiwan), December 2018.
    Attractiveness estiamtionn method of food photos using gaze information (in Japanese)
    Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
    IEICE SIG Attractiveness Computing Symposium 2018, Osaka Inst. of Tech., Umeda campus, September 2018.
    Estimating the attractiveness of a food photo using a Convolutional Neural Network (in Japanese)
    Akinori Sato, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase
    IEICE Tech. Rep. Media Experience and Virtual Environment, MVE2017-32, Kitami Institute of Technology, October 2017.
    Improvement of an attractiveness of food photos by using gaze information during preference experiment (in Japanese)
    Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
    Proc. 2017 Electric / Electronic / Information Engineering Related Society Tokai Sectors Joint Convention, G3-4, Nagoya Univ., September 2017.
    TBA (in Japanese)
    Akinori Sato, Takatsugu Hirayama, Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
    IPSJ Tech. Rep. Computer Vision and Image Media, 2017-CVIM-207-36, Nagoya Univ., May 2017.


Last updated: 2021-05-13 11:06:07.648959724 +0900 JST m=+0.875612905.