IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

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 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)
Download PDF 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)  
Keyword(1) Deep learning model  
Keyword(2) Subjective rating prediction  
Keyword(3) Food image  
Keyword(4) Visual judgement of taste  
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  
5th Author's Affiliation Tohoku University (Tohoku Univ.)
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
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 
Date of Issue 2021-02-25 (EMM) 

[Return to Top Page]

[Return to IEICE Web Page]

The Institute of Electronics, Information and Communication Engineers (IEICE), Japan