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Paper Abstract and Keywords
Presentation 2018-03-18 11:10
Simultaneous Learning Model of Food Image Recognition and Ingrediensts Estimation
Koyo Ito, Takao Yamanaka (Sophia Univ.) BioX2017-38 PRMU2017-174
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, many health-care applications such as food diary have been developed for smart devices. It is important for the applications to recognize the food category and the ingredients from a food image. In the generic object recognition, the accuracy has been dramatically improved by the deep convolutional neural networks(CNN). Using CNN, the food recognition has been successfully developed by learning both
the food image recognition task and the ingredients estimation task, simultaneously. However, only the simple models have been studied in the previous works. In this paper, novel models using CNN have been
proposed for the simultaneous learning of the food image recognition and the ingredients estimation. As results of the evaluation experiments, the accuracy was improved in the most of the proposed methods from the existing models. In the proposed models, the food recognition was improved by 1.4%, while the accuracy of the ingredients estimation was increased by 1.82% for Micro-F1 and 6.52% for Macro-F1.
Keyword (in Japanese) (See Japanese page) 
(in English) food image recognition / ingredients estimation / convolutional neural network / multi-task CNN / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 514, PRMU2017-174, pp. 13-18, March 2018.
Paper # PRMU2017-174 
Date of Issue 2018-03-11 (BioX, PRMU) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 PRMU BioX  
Conference Date 2018-03-18 - 2018-03-19 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2018-03-PRMU-BioX 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Simultaneous Learning Model of Food Image Recognition and Ingrediensts Estimation 
Sub Title (in English)  
Keyword(1) food image recognition  
Keyword(2) ingredients estimation  
Keyword(3) convolutional neural network  
Keyword(4) multi-task CNN  
1st Author's Name Koyo Ito  
1st Author's Affiliation Sophia University (Sophia Univ.)
2nd Author's Name Takao Yamanaka  
2nd Author's Affiliation Sophia University (Sophia Univ.)
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Date Time 2018-03-18 11:10:00 
Presentation Time 25 
Registration for PRMU 
Paper # IEICE-BioX2017-38,IEICE-PRMU2017-174 
Volume (vol) IEICE-117 
Number (no) no.513(BioX), no.514(PRMU) 
Page pp.13-18 
#Pages IEICE-6 
Date of Issue IEICE-BioX-2018-03-11,IEICE-PRMU-2018-03-11 

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