【24h】

Real-time Traffic Signs Detection Based on YOLO Network Model

机译:基于YOLO网络模型的实时交通标志检测

获取原文

摘要

Recently, real-time traffic sign detection has been widely applied in autonomous and assisted car driving. At the same time, the research on traffic signs detection based on YOLO (You Only Look Once) has attracted intensive attention. However, the accuracy and precision of small targets detection based on YOLO need to be further improved. We trained and tested the latest YOLOv4 and YOLOv3 on the same data set to comparatively study the detection results. The data set consists of 4000 Chinese traffic signs, which were manually labeled by ourselves. Comparing the detection results, the detection accuracy of the V4 is significantly higher than that of the V3.
机译:最近,实时交通标志检测已被广泛应用于自主和辅助汽车驾驶。与此同时,基于YOLO(你只看一次)的交通标志检测研究引起了密集的关注。然而,基于YOLO的小目标检测的精度和精度需要进一步提高。我们在同一数据集中培训并测试了最新的YOLOV4和YOLOV3,以比较研究检测结果。数据集由4000个中国交通标志组成,由我们自己手动标记。比较检测结果,V4的检测精度明显高于V3的检测精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号