On proprietary SEM wafer images, unsupervised domain adaptation methods such as offline pseudo-labeling and AdaMatch improve defect classification accuracy across product technologies, but the proposed DBACS method often underperforms the no-adaptation baseline.
A deep convolutional autoencoder-based approach for anomaly detection with industrial, non-images, 2-dimensional data: A semiconductor manufacturing case study
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Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing
On proprietary SEM wafer images, unsupervised domain adaptation methods such as offline pseudo-labeling and AdaMatch improve defect classification accuracy across product technologies, but the proposed DBACS method often underperforms the no-adaptation baseline.