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Paper Abstract and Keywords
Presentation 2025-03-05 14:00
A Consideration on Applying Fine-tuning to Reduce Subject Burden in Subjective Evaluation Estimation of Video Viewers Using Bio-signals
Keita Izawa, Wataru Kameyama (Waseda Univ.) CQ2024-98
Abstract (in Japanese) (See Japanese page) 
(in English) In subjective evaluation estimation of video viewers using bio-signals, increasing the number of viewed videos is effective in improving accuracy, but it also leads to increasing the burden of subjects because it requires their more cooperation. Therefore, in this paper, we apply Fine-tuning to a pretrained model constructed from all subjects’ data except for the target subject, and examine whether the same estimation accuracy can be obtained with a small amount of data from the target subject. As a result of the experiments using DEAP dataset, we confirm that the accuracy of the four subjective evaluations, i.e. Valence, Arousal, Dominance, and Liking, tends to be more than the baseline accuracy with half the number of videos. And we also confirm that the accuracy is further improved by applying Fast Fourier Transform to calculate EEG-related information and dimensionality reduction with Principal Component Analysis. Therefore, it is suggested that applying Fine-tuning to a pretrained model constructed from all subjects’ data except for the target subject may reduce the burden on subjects.
Keyword (in Japanese) (See Japanese page) 
(in English) Subjective Evaluation Estimation / Machine Learning / Fine-tuning / Bio-signals / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 404, CQ2024-98, pp. 39-44, March 2025.
Paper # CQ2024-98 
Date of Issue 2025-02-26 (CQ) 
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 CQ2024-98

Conference Information
Committee MVE CQ IMQ IE  
Conference Date 2025-03-05 - 2025-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2025-03-MVE-CQ-IMQ-IE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Consideration on Applying Fine-tuning to Reduce Subject Burden in Subjective Evaluation Estimation of Video Viewers Using Bio-signals 
Sub Title (in English)  
Keyword(1) Subjective Evaluation Estimation  
Keyword(2) Machine Learning  
Keyword(3) Fine-tuning  
Keyword(4) Bio-signals  
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1st Author's Name Keita Izawa  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Wataru Kameyama  
2nd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2025-03-05 14:00:00 
Presentation Time 20 minutes 
Registration for CQ 
Paper # CQ2024-98 
Volume (vol) vol.124 
Number (no) no.404 
Page pp.39-44 
#Pages 6 
Date of Issue 2025-02-26 (CQ) 

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