Paper Abstract and Keywords |
Presentation |
2022-03-11 17:55
A study on multi-task learning toward attractiveness estimation for food photography Mitsuaki Miyazaki, Keisuke Doman (Chukyo Univ.), Ichiro Ide (Nagoya Univ.), Yoshito Mekada (Chukyo Univ.) IMQ2021-68 IE2021-130 MVE2021-97 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
We report the results of a study on multi-task learning for the accuracy improvement of attractiveness estimation of food photography. We have been studying a way of improving the estimation accuracy by effectively using a small-scale image dataset. This paper proposes another approach based on multi-task learning for attractiveness estimation. Multi-task learning is a method that simultaneously learns multiple tasks within one model. Solving a task of interest together with its related tasks can improve the generalization performance of a trained model compared to solving each task independently. Thus, we expect that such a multi-task approach is effective for the attractiveness estimation of food photography. This report proposes a multi-task learning method that simultaneously solves multiple problems including attractiveness estimation as the main task and related estimation/classification problems as subtasks, and also confirm its effectiveness through evaluation experiments. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Food photography / attractiveness estimation / multi-task learning / regression analysis / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 423, MVE2021-97, pp. 306-311, March 2022. |
Paper # |
MVE2021-97 |
Date of Issue |
2022-03-02 (IMQ, IE, MVE) |
ISSN |
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) |
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IMQ2021-68 IE2021-130 MVE2021-97 |
Conference Information |
Committee |
CQ IMQ MVE IE |
Conference Date |
2022-03-09 - 2022-03-11 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online (Zoom) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Media of five senses, Multimedia, Media experience, Picture codinge, Image media quality, Network,quality and reliability, etc |
Paper Information |
Registration To |
MVE |
Conference Code |
2022-03-CQ-IMQ-MVE-IE |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A study on multi-task learning toward attractiveness estimation for food photography |
Sub Title (in English) |
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Keyword(1) |
Food photography |
Keyword(2) |
attractiveness estimation |
Keyword(3) |
multi-task learning |
Keyword(4) |
regression analysis |
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1st Author's Name |
Mitsuaki Miyazaki |
1st Author's Affiliation |
Chukyo University (Chukyo Univ.) |
2nd Author's Name |
Keisuke Doman |
2nd Author's Affiliation |
Chukyo University (Chukyo Univ.) |
3rd Author's Name |
Ichiro Ide |
3rd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
4th Author's Name |
Yoshito Mekada |
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Chukyo University (Chukyo Univ.) |
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Speaker |
Author-1 |
Date Time |
2022-03-11 17:55:00 |
Presentation Time |
25 minutes |
Registration for |
MVE |
Paper # |
IMQ2021-68, IE2021-130, MVE2021-97 |
Volume (vol) |
vol.121 |
Number (no) |
no.420(IMQ), no.422(IE), no.423(MVE) |
Page |
pp.306-311 |
#Pages |
6 |
Date of Issue |
2022-03-02 (IMQ, IE, MVE) |
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