A U-Net trained on CAD layouts and flawed wafer photos can generate defect-free synthetic wafer images that serve as a template for automated defect detection in InP multi-project wafer manufacturing.
Hyperspectral anomaly detection method based on auto-encoder, in: Image and Signal Processing for Remote Sensing XXI, Spie
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Deep Learning-based Multi Project InP Wafer Simulation for Unsupervised Surface Defect Detection
A U-Net trained on CAD layouts and flawed wafer photos can generate defect-free synthetic wafer images that serve as a template for automated defect detection in InP multi-project wafer manufacturing.