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GAN Applications in Defect Detection by Jeremy is a document available to read on EtoBox.
What is GAN Applications in Defect Detection about?
This paper reviews the application of Generative Adversarial Networks (GAN) in defect detection across various industries, highlighting its advantages over traditional supervised learning methods, particularly in scenarios with limited defect samples. It discusses the theoretical foundations, technical developments, and practical applications of GAN in defect detection, while also addressing existing challenges and future research directions. The paper aims to provide valuable insights for researchers inter
- Author
- Jeremy
- Language
- EN