Inception meets Swin Transformer: A Novel Approach for Metal Defect Recognition
Donglin Tang,
Yunliang Zhao
Abstract:The detection of metal defects with high precision and efficiency is a significant challenge in modern industry. Existing machine learning methods for recognizing common metal surface defects heavily rely on expert knowledge for manual feature extraction. Conventional deep learning methods face challenges in capturing global feature information from defect images or defect detection signals.To address this issue, we proposed a metal defect recognition method based on an Inception-fused Swin Transformer model. … Show more
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