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CNN requires less feature engineering but still needs preprocessing, e.g., denoising and resizing. Denoising is used to improve the quality of the input data, and resizing is used to transform the input into an identical size when the input data sizes are various. However, denoising and resizing may distort the original data information. Nevertheless, CNN-based applications are focusing on studying different feature map architectures and the input data manipulation is less attractive. In this study, we proposed an image hash layer triggered CNN framework for wafer map failure pattern retrieval and classification. The motivation and novelty are to design a CNN layer that can play as a resizing, information retrieval-preservation method in one step. The experiments proved that the proposed hash layer can retrieve the failure pattern information while maintaining the classification performance even though the input data size is decreased significantly. In the meantime, it can prevent overfitting, false negatives, and false positives, and save computing costs to a certain extent.<\/jats:p>","DOI":"10.1145\/3638053","type":"journal-article","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T11:53:11Z","timestamp":1702986791000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Image Hash Layer Triggered CNN Framework for Wafer Map Failure Pattern Retrieval and Classification"],"prefix":"10.1145","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7348-0752","authenticated-orcid":false,"given":"Minghao","family":"Piao","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Soochow University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4652-805X","authenticated-orcid":false,"given":"Yi","family":"Sheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Soochow University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8900-2501","authenticated-orcid":false,"given":"Jinda","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Soochow University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5611-0637","authenticated-orcid":false,"given":"Cheng Hao","family":"Jin","sequence":"additional","affiliation":[{"name":"ENN Research Institute of Digital Technology, China"}]}],"member":"320","published-online":{"date-parts":[[2024,2,13]]},"reference":[{"issue":"1","key":"e_1_3_5_2_2","first-page":"50","article-title":"An improved capsule network (WaferCaps) for wafer bin map classification based on DCGAN data upsampling","volume":"35","author":"Rahman M. 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