Sedg-yolov5: a lightweight traffic sign detection model based on knowledge distillation

HIGHLIGHTS

  • who: Liang Zhao and colleagues from the College of Electrical Engineering, Henan University of Technology, Zhengzhou, China have published the paper: SEDG-Yolov5: A Lightweight Traffic Sign Detection Model Based on Knowledge Distillation, in the Journal: Electronics 2023, 12, 305. of /2023/
  • what: Inspired by the bottleneck structure and attention mechanism, the authors propose ESGBlock in this paper. A lightweight detection model is designed to implement real-time traffic sign detection in this paper. Instead of directly adding the teacher prediction loss to the student loss in the original method, the authors propose a weighted . . .

     

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