WaferSegClassNet - A light-weight network for classification and segmentation of semiconductor wafer defects

As the integration density and design intricacy of semiconductor wafers increase, the magnitude and complexity of defects in them are also on the rise. Since the manual inspection of wafer defects is costly, an automated artificial intelligence (AI) based computer-vision approach is highly desired....

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Veröffentlicht in:	Computers in industry Jg. 142; S. 103720
Hauptverfasser:	Nag, Subhrajit, Makwana, Dhruv, R, Sai Chandra Teja, Mittal, Sparsh, Mohan, C.Krishna
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2022
Schlagworte:	Convolution neural network Encoder-decoder architecture Image classification Image Segmentation Semiconductor wafer defect analysis Semiconductor wafer defect analysis Encoder-decoder architecture Convolution neural network Image Segmentation Image classification
ISSN:	0166-3615, 1872-6194
Online-Zugang:	Volltext
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