基于改进YOLOv5的小目标交通标志检测算法OA
Small Target Traffic Sign Detection Algorithm Based on Improved YOLOv5
针对小目标交通标志检测精度低的问题,提出基于改进YOLOv5的小目标交通标志检测算法.优化YO-LOv5的主干网络结构,采用微小目标检测层替换原始大目标检测层,调整下采样倍数,将MobileViT Block融入颈部网络,采用离线增强与在线增强的方法对数据集进行处理.实验结果表明:与其他目标检测算法相比,改进算法的小目标交通标志检测均值平均精度为85.3%,参数量降低了39%,FPS为70,满足实时检测的要求.
In order to improve the low detection accuracy of small target traffic signs,a small target traf-fic sign detection algorithm based on improved YOLOv5 was proposed.The backbone network structure of YOLOv5 was optimized,and the original large target detection layer was replaced with a small target detection layer.In addition,the down-sampling factor was adjusted,and the MobileViT Block module was integrated into the neck network.Then,the dataset was processed…查看全部>>
徐鑫;方凯
湖北汽车工业学院 电气与信息工程学院,湖北 十堰 442002湖北汽车工业学院 电气与信息工程学院,湖北 十堰 442002
交通运输
交通标志检测YOLOv5MobileVit Block小目标检测
traffic sign detectionYOLOv5MobileVit Blocksmall target detection
《湖北汽车工业学院学报》 2023 (4)
17-21,5
湖北省教育厅科学技术研究项目(D20201802)教育部产学研合作协同育人项目(202002009056)
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