Improved yolov4 for pedestrian detection and counting in uav images

HIGHLIGHTS

• who: UAV Images and collaborators from the School of Computer, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China have published the research: Improved YOLOv4 for Pedestrian Detection and Counting in UAV Images, in the Journal: Computational Intelligence and Neuroscience of 14/07/2022
• what: The authors propose an improved YOLOv4 model for pedestrian detection and counting in named YOLO-CC. The experiments demonstrate that YOLO-CC achieves 21.76 points AP50 higher than that of the original YOLOv4 on the VisDrone2021-counting data set while running faster than the original YOLOv4. The aim of . . .
  

   

  

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