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Paper Abstract and Keywords
Presentation 2026-01-30 10:45
Improving Classification Performance of Vision Transformer Solving Jigsaw Puzzle Task
Toshikazu Samura, Thanawit Gerdprasert (Yamaguchi Univ) NLP2025-118 MBE2025-58 NC2025-80
Abstract (in Japanese) (See Japanese page) 
(in English) Generally, achieving high classification performance with deep neural networks, such as Convolutional Neural Networks (CNNs) andVisionTransformers (ViTs), requires large-scale annotated datasets. In application fields involving non-standard data formats where annotation costs are high, it is difficult to use deep neural networks. Therefore, to expand the application field of CNNs and ViTs, it is crucial to develop methods deriving better performance even on small-scale annotated datasets. This study focuses on previous research that incorporates jigsaw puzzle tasks into ViTs. We demonstrate that simultaneously solving the class prediction and jigsaw puzzle tasks improves classification performance when training on small-scale datasets.
Keyword (in Japanese) (See Japanese page) 
(in English) Vision Transformer / Jigsaw Puzzle / Small-scale dataset / / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 344, NLP2025-118, pp. 157-159, Jan. 2026.
Paper # NLP2025-118 
Date of Issue 2026-01-21 (NLP, MBE, NC) 
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 NLP2025-118 MBE2025-58 NC2025-80

Conference Information
Committee NC MBE NLP IEE-MBE  
Conference Date 2026-01-28 - 2026-01-30 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyushu Institute of Technology, Wakamatsu Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) NC, NLP, ME, etc. 
Paper Information
Registration To NLP 
Conference Code 2026-01-NC-MBE-NLP-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improving Classification Performance of Vision Transformer Solving Jigsaw Puzzle Task 
Sub Title (in English)  
Keyword(1) Vision Transformer  
Keyword(2) Jigsaw Puzzle  
Keyword(3) Small-scale dataset  
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1st Author's Name Toshikazu Samura  
1st Author's Affiliation Yamaguchi University (Yamaguchi Univ)
2nd Author's Name Thanawit Gerdprasert  
2nd Author's Affiliation Yamaguchi University (Yamaguchi Univ)
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Speaker Author-1 
Date Time 2026-01-30 10:45:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2025-118, MBE2025-58, NC2025-80 
Volume (vol) vol.125 
Number (no) no.344(NLP), no.345(MBE), no.346(NC) 
Page pp.157-159 
#Pages 3 
Date of Issue 2026-01-21 (NLP, MBE, NC) 

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