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| Presentation | 2022-01-20 09:50 Classification method for painting defects using a two-step deep learning Kazune Adachi, Takahiro Natori, Naoyuki Aikawa (Tokyo Univ. of Science)  CAS2021-51 ICTSSL2021-28 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Recently, inspection methods for defect detection and classification using deep learning have been proposed. In this paper, we propose a classification method for painting defects using a two-step deep learning. In this method, the first step is to determine whether the defect is a painting defects or not, and the second step is to determine the kind of painting defect. We propose a two-step classification method using deep learning. We show that the accuracy of the proposed method is higher than that of the previously proposed method, which classifies all kinds of painting defects at once. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Painting defects / Visual inspection / Deep learning / Image processing / Two-step classification / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 325, CAS2021-51, pp. 1-5, Jan. 2022. | |
| Paper # | CAS2021-51 | |
| Date of Issue | 2022-01-13 (CAS, ICTSSL) | |
| 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 | CAS2021-51 ICTSSL2021-28 |
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| Conference Information | |
| Committee | ICTSSL CAS |
| Conference Date | 2022-01-20 - 2022-01-21 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | CAS |
| Conference Code | 2022-01-ICTSSL-CAS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Classification method for painting defects using a two-step deep learning |
| Sub Title (in English) | |
| Keyword(1) | Painting defects |
| Keyword(2) | Visual inspection |
| Keyword(3) | Deep learning |
| Keyword(4) | Image processing |
| Keyword(5) | Two-step classification |
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| 1st Author's Name | Kazune Adachi |
| 1st Author's Affiliation | Tokyo University of Science (Tokyo Univ. of Science) |
| 2nd Author's Name | Takahiro Natori |
| 2nd Author's Affiliation | Tokyo University of Science (Tokyo Univ. of Science) |
| 3rd Author's Name | Naoyuki Aikawa |
| 3rd Author's Affiliation | Tokyo University of Science (Tokyo Univ. of Science) |
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| Speaker | Author-1 |
| Date Time | 2022-01-20 09:50:00 |
| Presentation Time | 25 minutes |
| Registration for | CAS |
| Paper # | CAS2021-51, ICTSSL2021-28 |
| Volume (vol) | vol.121 |
| Number (no) | no.325(CAS), no.326(ICTSSL) |
| Page | pp.1-5 |
| #Pages | 5 |
| Date of Issue | 2022-01-13 (CAS, ICTSSL) |
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