Deep Convolutional Generative Adversarial Networks-Based Data Augmentation Method for Classifying Class-Imbalanced Defect Patterns in Wafer Bin Map

Deep Convolutional Generative Adversarial Networks-Based Data Augmentation Method for Classifying Class-Imbalanced Defect Patterns in Wafer Bin Map

In the semiconductor industry, achieving a high production yield is a very important issue. Wafer bin maps (WBMs) provide critical information for identifying anomalies in the manufacturing process. A WBM forms a certain defect pattern according to the error occurring during the process, and by accu...

Full description

Bibliographic Details
Main Authors: Sangwoo Park, Cheolwoo You
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Applied Sciences
Subjects:
wafer bin map
wafer defects
deep learning
data imbalance
data augmentation
Online Access:https://www.mdpi.com/2076-3417/13/9/5507

Internet

https://www.mdpi.com/2076-3417/13/9/5507

Similar Items