计算机应用与软件2024，Vol.41Issue(11)：327-334,8.DOI:10.3969/j.issn.1000-386x.2024.11.045
基于YOLOv4改进的交通标志检测算法
AN IMPROVED TRAFFIC SIGN DETECTION ALGORITHM BASED ON YOLOV4
摘要
Abstract
It is necessary to detect traffic signs as early as possible and make driving decisions in a timely manner in the automatic driving scene,traffic signs at this point are small targets.The detection accuracy of small traffic signs is low.In order to solve this problem,an improved traffic sign detection algorithm based on YOLOv4 is proposed.The improvement of the algorithm mainly included the following parts:the integrated attention module was embedded into the backbone network to strengthen the attention of channel and spatial information;the binary cross entropy loss function was changed to focal loss to solve the imbalance problem of positive and negative samples;multi-scale information of picture was used for feature extraction and dilated convolution increase receptive field.The proposed methods were trained and tested on TT00K dataset respectively.The experimental result shows that the total mAP of the improved network model is improved by 14.16%compared with the original YOLOV4,and its overall performance outperforms other detection methods.关键词
交通标志检测/注意力模块/损失函数/多尺度特征Key words
Traffic sign detection/Attention module/Cost function/Multi-scale information分类
信息技术与安全科学引用本文复制引用
李丹阳,刘卫光,强赞霞,肖顺亮..基于YOLOv4改进的交通标志检测算法[J].计算机应用与软件,2024,41(11):327-334,8.基金项目
河南省科技攻关项目(182102210126). （182102210126）
