A BiFPN-YOLOv8 for Rail Surface Defect Detection Network Model
Aiming to defect such as peeling,holes,scars,scratches,cracks and wear on the rail surface,a BiFPN-YOLOv8 rail surface defect detection network model is constructed.In the data preparation phase,the rail surface image data is augmented through Gauss noise transformation and rotation transformation;In the network construction phase,in order to improve the performance of rail surface defect detection,the BiFPN-YOLOv8 is constructed by introducing the weighted bidirectional pyramid structure BiFPN into the original YOLOv8 network model;In the experimental simulation phase,the quantitative comparison and qualitative detection result evaluation on the RSDDs data set illustrates the accuracy and applicability of the BiFPN-YOLOv8 network model in the rail surface defect detection task.
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