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Paper Abstract and Keywords
Presentation 2019-03-09 17:20
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Fumiya Kudo (SyntheMec), Souichiro Yokoyama, Tomohisa Yamashita, Hidenori Kawamura (Hokudai) AI2018-58
Abstract (in Japanese) (See Japanese page) 
(in English) Although inspection of defective products is generally conducted visually at the manufacturing site of industrial products, automation by AI technology is desired as inspection personnel's high human cost and aging become a problem There. In abnormality detection using AI technology, supervised learning using good product data and defective product data is often used, but at the manufacturing site of industrial products, since the incidence of defective products is low, collection of defective item data difficult. Therefore, in this research, we proposed a system of defect inspection using a convolutional auto encoder that unsupervised learning with good data only and verified its usefulness. Also, it has been shown that the proposed defect inspection system can be applied to various industrial products by constructing the image sampling environment from scratch.
Keyword (in Japanese) (See Japanese page) 
(in English) Inspection of defect / Convolutional Autoencoder / Unsupervised Learning / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 492, AI2018-58, pp. 31-36, March 2019.
Paper # AI2018-58 
Date of Issue 2019-03-04 (AI) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 AI IPSJ-ICS JSAI-KBS JSAI-DOCMAS JSAI-SAI  
Conference Date 2019-03-07 - 2019-03-10 
Place (in Japanese) (See Japanese page) 
Place (in English)  
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Paper Information
Registration To AI 
Conference Code 2019-03-AI-ICS-KBS-DOCMAS-SAI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Please fill in 
Sub Title (in English)  
Keyword(1) Inspection of defect  
Keyword(2) Convolutional Autoencoder  
Keyword(3) Unsupervised Learning  
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1st Author's Name Fumiya Kudo  
1st Author's Affiliation SyntheMec Co LTD (SyntheMec)
2nd Author's Name Souichiro Yokoyama  
2nd Author's Affiliation Hokkaido University (Hokudai)
3rd Author's Name Tomohisa Yamashita  
3rd Author's Affiliation Hokkaido University (Hokudai)
4th Author's Name Hidenori Kawamura  
4th Author's Affiliation Hokkaido University (Hokudai)
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Speaker Author-1 
Date Time 2019-03-09 17:20:00 
Presentation Time 20 minutes 
Registration for AI 
Paper # AI2018-58 
Volume (vol) vol.118 
Number (no) no.492 
Page pp.31-36 
#Pages 6 
Date of Issue 2019-03-04 (AI) 

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