High-Performance Fine Defect Detection in Artificial Leather Using Dual Feature Pool Object Detection
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In this study, the structural problems of the YOLOv5 model were analyzed emphatically. Based on the characteristics of fine defects in artificial leather, four innovative structures, namely DFP, IFF, AMP, and EOS, were designed. These advancements led to the proposal of a high-performance artificial leather fine defect detection model named YOLOD. YOLOD demonstrated outstanding performance on the artificial leather defect dataset, achieving an impressive increase of 11.7 significant reduction of 5.2 YOLOD also exhibited remarkable performance on the general MS-COCO dataset, with an increase of 0.4 4.1 YOLOD in both artificial leather defect detection and general object detection tasks, making it a highly efficient and effective model for real-world applications.
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