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Paper Abstract and Keywords
Presentation 2021-05-28 09:40
Self-supervised representation learning with grayscale images
Yuichiro Sumi, Takuto Kojima (Nagoya Univ.), Kentaro Kutsukake (RIKEN), Tetsuya Matsumoto, Hiroaki Kudo (Nagoya Univ.), Yoshinori Takeuchi (Daido Univ.), Noritaka Usami (Nagoya Univ.) IMQ2021-1
Abstract (in Japanese) (See Japanese page) 
(in English) Multicrystalline silicon solar cells, which are most commonly used in residential photovoltaic systems, include regions which show performance degradation due to the generation of dislocation clusters in silicon ingot. In this study, we performed self-supervised learning of ResNet using grayscale images such as PL (photoluminescence) or CT images, which are inherently intensity information, and investigated whether the features obtained by the self-supervised learning are useful for transfer learning for grayscale images. We performed transfer learning on the self-supervised ResNet using 45,000 grayscale transformed CIFAR-10 images for training, 5,000 for validation, and 10,000 for testing, and obtained a correct response rate of 64.7 %. When the transfer learning was conducted using 5,514 silicon PL images for training, 551 for verification, and 3,125 for testing, the correct response rate was 73.0 %.
Keyword (in Japanese) (See Japanese page) 
(in English) self-supervised learning / convolutional neural network / multicrystalline silicon / photoluminescence image / dislocation / generation point / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 48, IMQ2021-1, pp. 1-4, May 2021.
Paper # IMQ2021-1 
Date of Issue 2021-05-21 (IMQ) 
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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Conference Information
Committee IMQ  
Conference Date 2021-05-28 - 2021-05-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IMQ 
Conference Code 2021-05-IMQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Self-supervised representation learning with grayscale images 
Sub Title (in English)  
Keyword(1) self-supervised learning  
Keyword(2) convolutional neural network  
Keyword(3) multicrystalline silicon  
Keyword(4) photoluminescence image  
Keyword(5) dislocation  
Keyword(6) generation point  
Keyword(7)  
Keyword(8)  
1st Author's Name Yuichiro Sumi  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Takuto Kojima  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Kentaro Kutsukake  
3rd Author's Affiliation Institute of Physical and Chemical Research (RIKEN)
4th Author's Name Tetsuya Matsumoto  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name Hiroaki Kudo  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
6th Author's Name Yoshinori Takeuchi  
6th Author's Affiliation Daido University (Daido Univ.)
7th Author's Name Noritaka Usami  
7th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2021-05-28 09:40:00 
Presentation Time 25 minutes 
Registration for IMQ 
Paper # IMQ2021-1 
Volume (vol) vol.121 
Number (no) no.48 
Page pp.1-4 
#Pages 4 
Date of Issue 2021-05-21 (IMQ) 

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