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Paper Abstract and Keywords
Presentation 2026-03-18 16:20
Development of a Deep Learning-Based System for Fault Detection and Localization in Solar Panels
Honda Kiyoto, Kitamura takuya (NIT, Toyama) MSS2025-60 NLP2025-141
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, drones have been widely used for automated inspection of photovoltaic power plants. However, manual visual inspection of the captured video footage imposes a significant burden on operators, and efficient and reliable anomaly detection methods are required. In this paper, we propose a system that automatically identifies anomalous photo
voltaic panels by integrating anomaly detection using a pre-trained deep learning model with drone position estimation based on a panel layout map. In the proposed system, an anomaly detection model is constructed by annotating images extracted from drone videos, and a position estimation model is developed to estimate the drone location for each frame. The effectiveness of the proposed integrated system is evaluated through computer experiments using real-world data.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep learning / Anomaly detection / Position estimation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 417, MSS2025-60, pp. 71-76, March 2026.
Paper # MSS2025-60 
Date of Issue 2026-03-11 (MSS, NLP) 
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 MSS2025-60 NLP2025-141

Conference Information
Committee MSS NLP  
Conference Date 2026-03-18 - 2026-03-19 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MSS 
Conference Code 2026-03-MSS-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Development of a Deep Learning-Based System for Fault Detection and Localization in Solar Panels 
Sub Title (in English)  
Keyword(1) Deep learning  
Keyword(2) Anomaly detection  
Keyword(3) Position estimation  
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1st Author's Name Honda Kiyoto  
1st Author's Affiliation National Institute of Technology, Toyama (NIT, Toyama)
2nd Author's Name Kitamura takuya  
2nd Author's Affiliation National Institute of Technology, Toyama (NIT, Toyama)
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Speaker Author-1 
Date Time 2026-03-18 16:20:00 
Presentation Time 20 minutes 
Registration for MSS 
Paper # MSS2025-60, NLP2025-141 
Volume (vol) vol.125 
Number (no) no.417(MSS), no.418(NLP) 
Page pp.71-76 
#Pages 6 
Date of Issue 2026-03-11 (MSS, NLP) 

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