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Paper Abstract and Keywords
Presentation 2022-09-15 15:45
Comparison of results for different datasets of facial attractiveness features extracted using gradient-weighted class activation mapping
Takanori Sano (Keio Univ.) AI2022-24
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, research using deep learning to analyze faces to identify the features that make up facial attractiveness has attracted much attention. However, the differences in results depending on the dataset used for analysis have not been studied in detail. In this study, I constructed convolutional neural network models for each dataset using two datasets and visualized the features important for prediction using the gradient-weighted class activation mapping method. The results showed that, for both datasets, the eye region tended to be activated in highly attractive female images, which is consistent with findings in psychology. This approach is expected to contribute to understanding highly universal features in facial attractiveness and contribute to various engineering applications in addition to extending psychological findings.
Keyword (in Japanese) (See Japanese page) 
(in English) Facial attractiveness / Psychology / Grad-CAM / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 186, AI2022-24, pp. 37-41, Sept. 2022.
Paper # AI2022-24 
Date of Issue 2022-09-08 (AI) 
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)
Download PDF AI2022-24

Conference Information
Committee AI  
Conference Date 2022-09-15 - 2022-09-16 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To AI 
Conference Code 2022-09-AI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Comparison of results for different datasets of facial attractiveness features extracted using gradient-weighted class activation mapping 
Sub Title (in English)  
Keyword(1) Facial attractiveness  
Keyword(2) Psychology  
Keyword(3) Grad-CAM  
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1st Author's Name Takanori Sano  
1st Author's Affiliation Keio University (Keio Univ.)
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Speaker Author-1 
Date Time 2022-09-15 15:45:00 
Presentation Time 20 minutes 
Registration for AI 
Paper # AI2022-24 
Volume (vol) vol.122 
Number (no) no.186 
Page pp.37-41 
#Pages 5 
Date of Issue 2022-09-08 (AI) 

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