Paper Abstract and Keywords |
Presentation |
2020-12-17 15:25
Visual inspection system with a small number of anomalous data using DevNet Katsuhisa Kitaguchi, Yohei Nishizaki, Mamoru Saito (ORIST) PRMU2020-47 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
A good visual inspection using deep learning needs to collect a large amount of anomalous data. To solve this problem, we considered applying DevNet, which detects anomalies using few anomaly data, to automatic visual inspection. An experiment to identify scratch data sets of industrial products was conducted using the proposed method. Our method shows higher discrimination performance than a conventional data augmentation method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
CNN / Visual inspection / Metal parts / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 300, PRMU2020-47, pp. 53-57, Dec. 2020. |
Paper # |
PRMU2020-47 |
Date of Issue |
2020-12-10 (PRMU) |
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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PRMU2020-47 |
Conference Information |
Committee |
PRMU |
Conference Date |
2020-12-17 - 2020-12-18 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Transfer learning and few shot learning |
Paper Information |
Registration To |
PRMU |
Conference Code |
2020-12-PRMU |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Visual inspection system with a small number of anomalous data using DevNet |
Sub Title (in English) |
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CNN |
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Visual inspection |
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Metal parts |
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1st Author's Name |
Katsuhisa Kitaguchi |
1st Author's Affiliation |
Osaka Research Institute of Industrial Science and Technology (ORIST) |
2nd Author's Name |
Yohei Nishizaki |
2nd Author's Affiliation |
Osaka Research Institute of Industrial Science and Technology (ORIST) |
3rd Author's Name |
Mamoru Saito |
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Osaka Research Institute of Industrial Science and Technology (ORIST) |
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Speaker |
Author-1 |
Date Time |
2020-12-17 15:25:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2020-47 |
Volume (vol) |
vol.120 |
Number (no) |
no.300 |
Page |
pp.53-57 |
#Pages |
5 |
Date of Issue |
2020-12-10 (PRMU) |
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