Wafer Bin Map Defect Classification Using Semi-Supervised Learning


A new technical paper titled "Semi-Supervised Learning with Wafer-Specific Augmentations for Wafer Defect Classification" was published by researchers at Korea University. Abstract "Semi-supervised learning (SSL) models, which leverage both labeled and unlabeled datasets, have been increasingly applied to classify wafer bin map patterns in semiconductor manufacturing. These models typical... » read more

Are Better Machine Training Approaches Ahead?


We live in a time of unparalleled use of machine learning (ML), but it relies on one approach to training the models that are implemented in artificial neural networks (ANNs) — so named because they’re not neuromorphic. But other training approaches, some of which are more biomimetic than others, are being developed. The big question remains whether any of them will become commercially viab... » read more