Enhanced Stacked Denoising Autoencoder-Based Feature Learning for Recognition of Wafer Map Defects

In semiconductor manufacturing systems, defects on wafer maps tend to cluster and then these spatial patterns provide important process information for helping operators in finding out root-causes of abnormal processes. Promptly recognizing wafer map defects is an effective way to increase manufactu...

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Veröffentlicht in:	IEEE transactions on semiconductor manufacturing Jg. 32; H. 4; S. 613 - 624
1. Verfasser:	Yu, Jianbo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Deep learning defect recognition Defects Feature extraction Feature recognition Learning systems Machine learning manifold regularization Manifolds Manufacturing Manufacturing processes Noise reduction Pattern recognition Regularization stacked denoising autoencoder Wafer map
ISSN:	0894-6507, 1558-2345
Online-Zugang:	Volltext
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