Track Defect Detection Based on Neural Network

The maintenance and inspection of the high-speed railway is the core problem of railway safety. To solve the problems of insufficient network depth and low defect extraction ability, an improved Unet network model was proposed. in view of the relatively small defect area, the attention mechanism is used to effectively suppress the background and highlight the significant features of the defect. The experimental results show that the improved Unet model improves the comprehensive detection accuracy of defect targets by 6% compared with similar segmentation models.