It is of great significance to accurately detect small target traffic signs at real time in the field of autonomous driving.Aiming at problems such as low accuracy and missing detection of small target traf-fic signs by YOLOv5s algorithm,a traffic sign detection algorithm based on improved YOLOv5s was proposed.Transformer coding structure is combined with C3 module to replace the last C3 module in the trunk network with a new C3TR to improve the trunk network's ability to extract global feature infor-mation of images.EIoULoss was used to replace the positioning loss function of YOLOv5s to improve the regression accuracy of the model detection frame.In the multi-scale detection part,a shallow detec-tion layer is added as the detection layer of smaller targets to improve the detection ability of traffic signs.The experimental results show that the mean precision (mAP)of the improved YOLOv5s detec-tion algorithm on the CCTSDB data set is 93.1％,which is 3.6％ higher than the original YOLOv5s de-tection algorithm,and the detection accuracy of small-target traffic signs is higher.
small objecttraffic sign detectionYOLOv5smultiscale detection
万方数据
维普
