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Paper Abstract and Keywords
Presentation 2024-03-12 13:55
Identification of filamentous fungi by segmentation models using consistency regularization and classmix
Taiga Shimizu (Yamanashi Univ.), Waleed Asghar (Oklahoma State Univ.), Ryota Kataoka, Motonobu Hattori (Yamanashi Univ.) NC2023-57
Abstract (in Japanese) (See Japanese page) 
(in English) In agriculture, soil diagnosis is necessary to protect the environment. However, since current diagnostic methods are not very accurate and expensive, there is a need for simpler diagnostic methods.
In this study, we propose to apply the segmentation model, which has been used in various fields in recent years, to classify filamentous fungi collected from soil and cultured, and to use it as a diagnostic method.
Considering that learning original data for segmentation models involves significant costs for label assignment and preparation of training data, we incorporated several combinations of consistency regularization, one of the semi-supervised learning methods, into the learning process.
As a result, we confirmed that the proposed method improves identification accuracy by about 5% compared to general semi-supervised learning, and found that it has the potential to be used as one of the diagnostic methods.
Keyword (in Japanese) (See Japanese page) 
(in English) Segmentation / Semi-Supervised Learning / Consistency Regularization / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 418, NC2023-57, pp. 81-86, March 2024.
Paper # NC2023-57 
Date of Issue 2024-03-04 (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 NC2023-57

Conference Information
Committee NC MBE  
Conference Date 2024-03-11 - 2024-03-12 
Place (in Japanese) (See Japanese page) 
Place (in English) The Univ. of Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Brain architecture, General 
Paper Information
Registration To NC 
Conference Code 2024-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Identification of filamentous fungi by segmentation models using consistency regularization and classmix 
Sub Title (in English)  
Keyword(1) Segmentation  
Keyword(2) Semi-Supervised Learning  
Keyword(3) Consistency Regularization  
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1st Author's Name Taiga Shimizu  
1st Author's Affiliation Yamanashi University (Yamanashi Univ.)
2nd Author's Name Waleed Asghar  
2nd Author's Affiliation Oklahoma State Universityy (Oklahoma State Univ.)
3rd Author's Name Ryota Kataoka  
3rd Author's Affiliation Yamanashi University (Yamanashi Univ.)
4th Author's Name Motonobu Hattori  
4th Author's Affiliation Yamanashi University (Yamanashi Univ.)
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Speaker Author-1 
Date Time 2024-03-12 13:55:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2023-57 
Volume (vol) vol.123 
Number (no) no.418 
Page pp.81-86 
#Pages 6 
Date of Issue 2024-03-04 (NC) 

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