火力与指挥控制2024，Vol.49Issue(9)：90-96,103,8.DOI:10.3969/j.issn.1002-0640.2024.09.013
YOLOv5-CCE:一种基于CA和EIoU的目标检测算法
YOLOv5-CCE:an Object Detection Algorithm Based on CA and EIoU
摘要
Abstract
In order to reduce the false detection rate and missed detection rate of the YOLOv5 model in complex environments,a target detection model YOLOv5-CCE based on CA(Coordinate Attention)and EIoU(Efficient Intersection over Union)is proposed.Firstly,the coordinate attention mechanism CA is embedded in partial C3_2 module in the Neck network to enhance the feature extraction ability of the model;secondly,to improve the regression accuracy,an improved Focal CEIoU Loss based on Focal EIoU Loss is proposed.The experimental results show that on the PASCAL VOC 2007+2012 data set,the YOLOv5-CCE model maintains the parameters and calculations basically unchanged,compared with the original model of mAP@0.5 and mAP@0.5:0.95 and the accuracy rate respectively,its accuracy rate has increased by 1.4%,1.3%and 3.7%respectively.Therefore,the YOLOv5-CCE model can better adapt to the target detection task in complex envi-ronments.关键词
YOLOv5算法/EIoU/Focal Loss/CA注意力机制/目标检测Key words
YOLOv5 algorithm/EIoU/Focal Loss/CA attention mechanism/object detection分类
信息技术与安全科学引用本文复制引用
王军,黄博文,蔡景贵..YOLOv5-CCE:一种基于CA和EIoU的目标检测算法[J].火力与指挥控制,2024,49(9):90-96,103,8.基金项目
辽宁省自然科学基金(2022-MS-291) （2022-MS-291）
辽宁省教育厅科研基金(LJ2020024) （LJ2020024）
中国高校产学研创新基金(2021LD06009) （2021LD06009）
辽宁省教育厅科研基金资助项目(LJKMZ20220781) （LJKMZ20220781）
