Jia-Yu Xie

Application of a GAN model incorporating transfer learning methods for the detection of forming defects in metallic materials

Defect detection is essential for quality assurance in metal forming, but traditional methods often suffer from process complexity and imbalanced datasets. This study proposes a GAN-based defect detection framework integrating transfer learning to improve accuracy and robustness. A pre-trained GAN is first employed to...