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| Paper Abstract and Keywords | ||
| Presentation | 2016-02-23 09:45 General Food Recognition Based on Hierarchical Deep Learning with Metadata Hokuto Kagaya, Kiyoharu Aizawa (UTokyo), Makoto Ogawa (foo.log)  ITS2015-74 IE2015-116 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Food image analysis is one of the key technology to record everyday meal automatically. FoodLog, the system we have been developing, made smartphone-based food-logging easier. Food recognition from a single image is still a very challenging task. The purpose of this study is to improve the accuracy of food recognition. We propose two solutions based on Deep Learning: a hierarchical method for food image classification and introduction of metadata. As a result, the accuracy of food recognition has improved by 2.68% compared to the baseline method. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | hierarchical image classification / deep learnign / food image recogntion / metadata / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 115, no. 459, IE2015-116, pp. 229-234, Feb. 2016. | |
| Paper # | IE2015-116 | |
| Date of Issue | 2016-02-15 (ITS, IE) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and 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) | |
| Download PDF | ITS2015-74 IE2015-116 |
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| Conference Information | |
| Committee | ITS IE ITE-AIT ITE-HI ITE-ME ITE-MMS ITE-CE |
| Conference Date | 2016-02-22 - 2016-02-23 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hokkaido Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | IE |
| Conference Code | 2016-02-ITS-IE-AIT-HI-ME-MMS-CE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | General Food Recognition Based on Hierarchical Deep Learning with Metadata |
| Sub Title (in English) | |
| Keyword(1) | hierarchical image classification |
| Keyword(2) | deep learnign |
| Keyword(3) | food image recogntion |
| Keyword(4) | metadata |
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| 1st Author's Name | Hokuto Kagaya |
| 1st Author's Affiliation | The University of Tokyo (UTokyo) |
| 2nd Author's Name | Kiyoharu Aizawa |
| 2nd Author's Affiliation | The University of Tokyo (UTokyo) |
| 3rd Author's Name | Makoto Ogawa |
| 3rd Author's Affiliation | foo.log Inc. (foo.log) |
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| Speaker | Author-1 |
| Date Time | 2016-02-23 09:45:00 |
| Presentation Time | 15 minutes |
| Registration for | IE |
| Paper # | ITS2015-74, IE2015-116 |
| Volume (vol) | vol.115 |
| Number (no) | no.458(ITS), no.459(IE) |
| Page | pp.229-234 |
| #Pages | 6 |
| Date of Issue | 2016-02-15 (ITS, IE) |
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