An Attention-Augmented Convolutional Neural Network With Focal Loss for Mixed-Type Wafer Defect Classification

An Attention-Augmented Convolutional Neural Network With Focal Loss for Mixed-Type Wafer Defect Classification

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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: Uzma Batool, Mohd Ibrahim Shapiai, Salama A. Mostafa, Mohd Zamri Ibrahim
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Anomaly detection
deep learning
mixed-type defects
multi-defect classification
pattern recognition
channel attention
Online Access:https://ieeexplore.ieee.org/document/10268403/

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