HIGHLIGHTS
- who: Zexuan Guo and collaborators from the School of Modern Post, Beijing University of Posts and Telecommunications, Beijing, China have published the paper: MSFT-YOLO: Improved YOLOv5 Based on Transformer for Detecting Defects of Steel Surface, in the Journal: Sensors 2022, 3467 of 20/02/2022
- what: The experiments show that the improved MSFT-YOLO network structure can reach 75.7 mAP on the NEU-DET dataset, which is able to maintain the detection accuracy while maintaining the detection speed. The authors propose a steel surface defect detector called MSFT-YOLO based on YOLOv5. The . . .
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