Detection of foreign matter on high-speed train underbody based on deep learning

HIGHLIGHTS

• who: DEQIANG HE et al. from the School of Mechanical Engineering, University, Nanning, China have published the research: Detection of Foreign Matter on High-Speed Train Underbody Based on Deep Learning, in the Journal: (JOURNAL)
• what: At present, the inspection of foreign matter in the train bottom is mostly completed by artificial classification or conventional target recognition methods.
• how: In this work SSD and Faster R-CNN are used as the most representative algorithms of one-stage and two-stage algorithms respectively. In this paper four representative feature extractors based on deep convolutional . . .
  

   

  

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