An online rail track fastener classification system based on yolo models

HIGHLIGHTS

  • who: Chen-Chiung Hsieh and colleagues from the Department of Computer Science and Engineering, Tatung University, Taipei, Taiwan have published the Article: An Online Rail Track Fastener Classification System Based on YOLO Models, in the Journal: Sensors 2022, 22, x FOR PEER REVIEW of /2022/
  • what: The authors propose utilizing the YOLOv4-Tiny neural network to identify track defects in real time. In the experiments data augmentation by a Cycle Generative Adversarial Network (GAN) is used to increase the dataset. This section is an introduction to the motivation and background of the research and the . . .

     

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