| Presentation | 2022-01-20 Classification method for painting defects using a two-step deep learning Kazune Adachi, Takahiro Natori, Naoyuki Aikawa, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | Painting defects / Visual inspection / Deep learning / Image processing / Two-step classification |
| Paper # | CAS2021-51,ICTSSL2021-28 |
| Date of Issue | 2022-01-13 (CAS, ICTSSL) |
| Conference Information | |
| Committee | ICTSSL / CAS |
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| Conference Date | 2022/1/20(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Koichi Gyoda(Shibaura Inst. of Tech.) / Hiroki Sato(Sony LSI Design) |
| Vice Chair | Munenari Inoguchi(Toyama Univ.) / Tomotaka Wada(Kansai Univ.) / Yoshinobu Maeda(Niigata Univ.) |
| Secretary | Munenari Inoguchi(Synspective) / Tomotaka Wada(Hiroshima City Univ.) / Yoshinobu Maeda(Sony LSI Design) |
| Assistant | Shunichi Yokoyama(Shinshu Univ.) / Motoi Yamaguchi(TECHNOPRO) / Yohei Nakamura(Hitachi) / Takahide Sato(Univ. of Yamanashi) / Yasutoshi Aibara(Murata Manufacturing) |
| Paper Information | |
| Registration To | Technical Committee on Information and Communication Technologies for Safe and Secure Life / Technical Committee on Circuits and Systems |
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| Language | JPN |
| 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 |
| 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) |
| Date | 2022-01-20 |
| Paper # | CAS2021-51,ICTSSL2021-28 |
| Volume (vol) | vol.121 |
| Number (no) | CAS-325,ICTSSL-326 |
| Page | pp.pp.1-5(CAS), pp.1-5(ICTSSL), |
| #Pages | 5 |
| Date of Issue | 2022-01-13 (CAS, ICTSSL) |