Defect detection for metal shaft surfaces based on an improved yolov5 algorithm and transfer learning

HIGHLIGHTS

  • who: Bi Li and Quanjie Gao from the Wuhan University of Science and Technology, Wuhan, China have published the research work: Defect Detection for Metal Shaft Surfaces Based on an Improved YOLOv5 Algorithm and Transfer Learning, in the Journal: Sensors 2023, 23, 3761. of /2023/
  • what: To address the problem of low efficiency for manual detection in the defect detection field for metal shafts the authors propose a deep learning defect detection method based on the improved YOLOv5 algorithm. The model acquires the region that needs to be focused on. This paper adopts BiFPN as . . .

     

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