| Presentation | 2019-03-09 Please fill in Fumiya Kudo, Souichiro Yokoyama, Tomohisa Yamashita, Hidenori Kawamura, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | Inspection of defect / Convolutional Autoencoder / Unsupervised Learning |
| Paper # | AI2018-58 |
| Date of Issue | 2019-03-02 (AI) |
| Conference Information | |
| Committee | AI / IPSJ-ICS / JSAI-KBS / JSAI-DOCMAS / JSAI-SAI |
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| Conference Date | 2019/3/7(4days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Tsunenori Mine(Kyushu Univ.) |
| Vice Chair | Daisuke Katagami(Tokyo Polytechnic Univ.) / Naoki Fukuta(Shizuoka Univ.) |
| Secretary | Daisuke Katagami(Ritsumeikan Univ.) / Naoki Fukuta(Univ. of Electro-Comm.) |
| Assistant | Yuko Sakurai(AIST) |
| Paper Information | |
| Registration To | Technical Committee on Artificial Intelligence and Knowledge-Based Processing / Special Interest Group on Intelligence and Complex Systems / Special Interest Group on Knowledge-Based Systems / Special Interest Group on Data Oriented Constructive Mining and Simulation / Special Interest Group on Society and Artificial Intelligence |
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| Language | JPN |
| 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 |
| 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) |
| Date | 2019-03-09 |
| Paper # | AI2018-58 |
| Volume (vol) | vol.118 |
| Number (no) | AI-492 |
| Page | pp.pp.31-36(AI), |
| #Pages | 6 |
| Date of Issue | 2019-03-02 (AI) |