Enhancing Defect Diagnosis and Localization in Wafer Map Testing Through Weakly Supervised Learning
Author:
Affiliation:
1. Southeast University,Nanjing,China
2. Anhui Polytechnic University,Wuhu,China
3. Ehime University,Matsuyama,Japan
4. Kyushu Institute of Technology,Iizuka,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10317938/10317940/10317989.pdf?arnumber=10317989
Reference20 articles.
1. Semi-supervised rotation-invariant representation learning for wafer map pattern analysis
2. A Semi-Supervised and Incremental Modeling Framework for Wafer Map Classification
3. Novel method for detection of mixed-type defect patterns in wafer maps based on a single shot detector algorithm
4. Applying Data Augmentation and Mask R-CNN-Based Instance Segmentation Method for Mixed-Type Wafer Maps Defect Patterns Classification
5. Wafer Map Failure Pattern Recognition and Similarity Ranking for Large-Scale Data Sets
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