YOLOv5

Xiang Jia1, Ying Tong2, Hongming Qiao2

  • 1China Telecom Corporation Limited Beijing Research Institute, Beijing, China. jiax11@chinatelecom.cn.

Scientific reports
|June 15, 2023
PubMed
概括

这项研究引入了一种改进的YOLOv5模型,用于在自动驾驶中更快,更准确地检测物体. 改进的探测器在KITTI数据集上实现了96.1%的准确性和202 FPS.

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