| Presentation | 2023-03-03 Explainable Deep Clustering for Wafer Defect Pattern Classification Yuki Okazaki, Hiroki Takahashi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Classification of specific defect patterns on semiconductor wafers is important in manufacturing processes. Recently, many classification methods based on clustering have been proposed. However, it is unclear whether generated clusters have high visual validity that captures features of defect patterns. This paper proposes Explainable Deep Clustering (EDC), which uses deep learning to perform explainable clustering. EDC generates clusters of wafer maps with similar defect patterns. Moreover, each cluster is explained using statistical features. Besides, the analysis results are fed back to the clustering to improve the clusters. The experimental results show that the proposed method generates clusters with high visual validity and performs highly accurate classification. We also show the explainability of the cluster features. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Wafer Map Defects / Clustering / Deep Clustering / Explainable |
| Paper # | PRMU2022-115,IBISML2022-122 |
| Date of Issue | 2023-02-23 (PRMU, IBISML) |
| Conference Information | |
| Committee | PRMU / IBISML / IPSJ-CVIM |
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| Conference Date | 2023/3/2(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Future University Hakodate |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Seiichi Uchida(Kyushu Univ.) / Masashi Sugiyama(Univ. of Tokyo) |
| Vice Chair | Takuya Funatomi(NAIST) / Mitsuru Anpai(Denso IT Lab.) / Toshihiro Kamishima(AIST) / Koji Tsuda(Univ. of Tokyo) |
| Secretary | Takuya Funatomi(CyberAgent) / Mitsuru Anpai(Univ. of Tokyo) / Toshihiro Kamishima(NTT) / Koji Tsuda(Hokkaido Univ.) |
| Assistant | Nakamasa Inoue(Tokyo Inst. of Tech.) / Yasutomo Kawanishi(Riken) / Yoshinobu Kawahara(Osaka Univ.) / Taiji Suzuki(Tokyo Inst. of Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Information-Based Induction Sciences and Machine Learning / Special Interest Group on Computer Vision and Image Media |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Explainable Deep Clustering for Wafer Defect Pattern Classification |
| Sub Title (in English) | |
| Keyword(1) | Wafer Map Defects |
| Keyword(2) | Clustering |
| Keyword(3) | Deep Clustering |
| Keyword(4) | Explainable |
| 1st Author's Name | Yuki Okazaki |
| 1st Author's Affiliation | The University of Electro-Communications(The Univ. of Electro-Communications) |
| 2nd Author's Name | Hiroki Takahashi |
| 2nd Author's Affiliation | The University of Electro-Communications(The Univ. of Electro-Communications) |
| Date | 2023-03-03 |
| Paper # | PRMU2022-115,IBISML2022-122 |
| Volume (vol) | vol.122 |
| Number (no) | PRMU-404,IBISML-405 |
| Page | pp.pp.299-304(PRMU), pp.299-304(IBISML), |
| #Pages | 6 |
| Date of Issue | 2023-02-23 (PRMU, IBISML) |