Research on steel rail surface defects detection based on improved yolov4 network

HIGHLIGHTS

• who: Zengzhen Mi from the Yunnan University, China have published the Article: Research on steel rail surface defects detection based on improved YOLOv4 network, in the Journal: (JOURNAL) of 09/02/2023
• how: The experimental dataset were obtained from Rail beam factory of Panzhihua Iron and Steel (Group) Company and network datasets where the self-acquired dataset were used for training and the RSDDs (Gan et_al 2017) network datasets were used for validation. This paper introduces four evaluation indexes Recall Rate (Rc or R) Precision Rate (Pr or P) F1 Value and Average Inspection Time . . .
  

   

  

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