Enterprise-grade ML platform for semiconductor wafer defect classification using ResNet-50 U-Net architecture with active learning.
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Updated
Mar 5, 2026 - Python
Enterprise-grade ML platform for semiconductor wafer defect classification using ResNet-50 U-Net architecture with active learning.
Mask-aware wafer defect classification using a DenseNet-based CNN with explicit geometry masking and Grad-CAM explainability.
Research-driven wafer defect classification framework combining classical ML and CNN-based approaches, with experimental analysis of few-shot learning under severe class imbalance and limited data regimes.
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