Paper Abstract and Keywords |
Presentation |
2021-03-05 10:20
Analysis of visual subjective evaluation for qualities of food taste using machine learning techniques Yoshiyuki Sato (Tohoku Univ.), Kazuya Matsubara, Yuji Wada (Ritsmeikan Univ.), Nobuyuki Sakai, Satoshi Shioiri (Tohoku Univ.) EMM2020-77 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this study, we conducted an experiment to collect human subjective judgments about taste (e.g. sweetness, spiciness) for visual food images. We constructed a deep learning model based on ResNet-50 model to learn the subjective rating data and showed that the model was able to predict most of the subjective ratings successfully. Furthermore, to investigate the image features that are relevant to human judgements, we analyzed representational similarity between activations in each layer of the model and human subjective ratings. We showed that the ratings for basic tastes have high relevance to lower-level image features and the ratings for other tastes have high relevance only to higher-level image features. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep learning model / Subjective rating prediction / Food image / Visual judgement of taste / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 418, EMM2020-77, pp. 58-62, March 2021. |
Paper # |
EMM2020-77 |
Date of Issue |
2021-02-25 (EMM) |
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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EMM2020-77 |
Conference Information |
Committee |
EMM |
Conference Date |
2021-03-04 - 2021-03-05 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Image and Sound Quality, Metrics for Perception and Recognition, Human Auditory and Visual System, etc. |
Paper Information |
Registration To |
EMM |
Conference Code |
2021-03-EMM |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Analysis of visual subjective evaluation for qualities of food taste using machine learning techniques |
Sub Title (in English) |
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Keyword(1) |
Deep learning model |
Keyword(2) |
Subjective rating prediction |
Keyword(3) |
Food image |
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Visual judgement of taste |
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1st Author's Name |
Yoshiyuki Sato |
1st Author's Affiliation |
Tohoku University (Tohoku Univ.) |
2nd Author's Name |
Kazuya Matsubara |
2nd Author's Affiliation |
Ritsmeikan University (Ritsmeikan Univ.) |
3rd Author's Name |
Yuji Wada |
3rd Author's Affiliation |
Ritsmeikan University (Ritsmeikan Univ.) |
4th Author's Name |
Nobuyuki Sakai |
4th Author's Affiliation |
Tohoku University (Tohoku Univ.) |
5th Author's Name |
Satoshi Shioiri |
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Tohoku University (Tohoku Univ.) |
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Speaker |
Author-1 |
Date Time |
2021-03-05 10:20:00 |
Presentation Time |
25 minutes |
Registration for |
EMM |
Paper # |
EMM2020-77 |
Volume (vol) |
vol.120 |
Number (no) |
no.418 |
Page |
pp.58-62 |
#Pages |
5 |
Date of Issue |
2021-02-25 (EMM) |
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