Name
Title | ||
|---|---|---|
Semi-supervised Wafer Map Pattern Recognition using Domain-Specific Data Augmentation and Contrastive Learning |
Abstract | ||
|---|---|---|
Wafer map pattern recognition is instrumental for detecting systemic manufacturing process issues. However, high cost in labeling wafer patterns renders it impossible to leverage large amounts of valuable unlabeled data in conventional machine learning based wafer map pattern prediction. We proposed a contrastive learning framework for semi-supervised learning and prediction of wafer map patterns.... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ITC50571.2021.00019 | 2021 IEEE International Test Conference (ITC) |
Keywords | DocType | ISSN |
wafer map pattern recognition,semi-supervised learning,contrastive learning | Conference | 1089-3539 |
ISBN | Citations | PageRank |
978-1-6654-1695-5 | 0 | 0.34 |
References | Authors | |
0 | 3 | |