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An attention-augmented convolutional neural network with focal loss for mixed-type wafer defect classification

Silicon wafer defect classification is crucial for improving fabrication and chip production. Although deep learning methods have been successful in single-defect wafer classification, the increasing complexity of the fabrication process has introduced the challenge of multiple defects on wafers, wh...

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Bibliographic Details
Main Authors: Batool, Uzma, Mohd Ibrahim, Shapiai, Mostafa, Salama A., Mohd Zamri, Ibrahim
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/40649/1/An%20attention-augmented%20convolutional%20neural%20network.pdf
http://umpir.ump.edu.my/id/eprint/40649/
https://doi.org/10.1109/ACCESS.2023.3321025
https://doi.org/10.1109/ACCESS.2023.3321025
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http://umpir.ump.edu.my/id/eprint/40649/1/An%20attention-augmented%20convolutional%20neural%20network.pdf
http://umpir.ump.edu.my/id/eprint/40649/
https://doi.org/10.1109/ACCESS.2023.3321025
https://doi.org/10.1109/ACCESS.2023.3321025

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