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Paper Abstract and Keywords
Presentation 2017-10-20 11:20
Estimating the attractiveness of a food photo using a Convolutional Neural Network
Akinori Sato (Nagoya Univ.), Keisuke Doman (Chukyo Univ.), Takatsugu Hirayama, Ichiro Ide, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase (Nagoya Univ.) MVE2017-32
Abstract (in Japanese) (See Japanese page) 
(in English) We have previously proposed a method for estimating the attractiveness of a food photo in order to assist a user to shoot attractive food photos. In this method, image features were extracted from food photos with attractiveness scores, and the attractiveness score of an input food photo was estimated in a regression framework. In this report, we describe the result of constructing an attractiveness estimator using a convolutional neural network (CNN) as a new approach to this method. Specifically, CNNs which transfer-learned each of the pre-trained models of VGG16, ResNet50 and Inception-v3 is constructed and used as an attractiveness estimator. From the results compared with the previous method, we confirmed that the attractiveness estimator based on the VGG16 pre-trained model was effective.
Keyword (in Japanese) (See Japanese page) 
(in English) Food photo / shooting support / attractiveness / convolutional neural networks / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 252, MVE2017-32, pp. 107-111, Oct. 2017.
Paper # MVE2017-32 
Date of Issue 2017-10-12 (MVE) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
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reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee MVE  
Conference Date 2017-10-19 - 2017-10-20 
Place (in Japanese) (See Japanese page) 
Place (in English) KitamiInstitute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MVE 
Conference Code 2017-10-MVE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Estimating the attractiveness of a food photo using a Convolutional Neural Network 
Sub Title (in English)  
Keyword(1) Food photo  
Keyword(2) shooting support  
Keyword(3) attractiveness  
Keyword(4) convolutional neural networks  
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1st Author's Name Akinori Sato  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Keisuke Doman  
2nd Author's Affiliation Chukyo University (Chukyo Univ.)
3rd Author's Name Takatsugu Hirayama  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Ichiro Ide  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name Yasutomo Kawanishi  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
6th Author's Name Daisuke Deguchi  
6th Author's Affiliation Nagoya University (Nagoya Univ.)
7th Author's Name Hiroshi Murase  
7th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker
Date Time 2017-10-20 11:20:00 
Presentation Time 25 
Registration for MVE 
Paper # IEICE-MVE2017-32 
Volume (vol) IEICE-117 
Number (no) no.252 
Page pp.107-111 
#Pages IEICE-5 
Date of Issue IEICE-MVE-2017-10-12 


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