CCP-YOLO: An Improved YOLOv11n Algorithm for Steel Surface Defect Detection
Highlights What are the main findings? CCP-YOLO improves YOLOv11n for steel surface defect detection by enhancing multi-scale feature extraction, heterogeneous feature fusion, spatial-detail-preserving context aggregation, and bounding box regression. The proposed model achieves 80.2% mAP50 on the NEU-DET dataset, impr...