Controlled comparison finds CV-QNN heads reach 79.7% accuracy versus 61.6% for DV-QNN heads on eight-class wafer defect classification, with largest gains on localized defects, though both trail the classical baseline of 85%.
IEEE Trans Semicond Manuf 28(1):1–12
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Bridging Quantum Computing Paradigms toward Semiconductor Yield: A Controlled CV-versus-DV Comparison on Wafer-Map Defect Classification
Controlled comparison finds CV-QNN heads reach 79.7% accuracy versus 61.6% for DV-QNN heads on eight-class wafer defect classification, with largest gains on localized defects, though both trail the classical baseline of 85%.