Semi-Supervised Learning Under Extreme Class Imbalance in Wafer Bin Map Defect Pattern Classification

The semiconductor industry faces significant challenges in wafer quality assessment due to the increasing complexity of device fabrication and the rise in inline defects and circuit failures. As manufacturing processes advance, conventional manual analysis of wafer bin maps (WBMs) has become impract...

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Principais autores:	Jinyong Jeong, Hyungu Kahng, Seoung Bum Kim
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2026-01-01
coleção:	IEEE Access
Assuntos:	Wafer bin map defect pattern classification semiconductor manufacturing semi-supervised learning class-imbalanced learning class-imbalanced semi-supervised learning
Acesso em linha:	https://ieeexplore.ieee.org/document/11368897/
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