现代信息科技2025，Vol.9Issue(5)：25-32,38,9.DOI:10.19850/j.cnki.2096-4706.2025.05.005
Attention-YOLOv5s:引入注意力机制的YOLOv5s算法
Attention-YOLOv5s:YOLOv5s Algorithm with Introduced Attention Mechanism
摘要
Abstract
In order to improve the accuracy of image object detection,a YOLOv5s object detection algorithm combined with the Attention Mechanism is proposed.Firstly,in response to the issues of local occlusion and the difficulty in detecting small objects,the Attention Mechanism is introduced into the backbone network of YOLOv5s to enhance the feature extraction capability of the object detection algorithm for important regions.Then,to reduce the model complexity and accelerate the network convergence speed,the SIoU loss function is used to replace the original CIoU loss function in YOLOv5s.Finally,comparative experiments are carried out between the improved model and the crowd detection algorithm to analyze the pedestrian detection capability of the model.The comparative experiments on the VOC2007 dataset show that the average accuracy of the improved YOLOv5s object detection algorithm reaches 70.5%,effectively improving pedestrian detection effect in complex backgrounds and achieving the lightweighting of the network simultaneously.关键词
YOLOv5s/目标检测/注意力机制/损失函数/行人检测Key words
YOLOv5s/Object Detection/Attention Mechanism/loss function/pedestrian detection分类
计算机与自动化引用本文复制引用
杨可帆,魏昕恺,马妍,王佳玲,宋涛,韦艳芳..Attention-YOLOv5s:引入注意力机制的YOLOv5s算法[J].现代信息科技,2025,9(5):25-32,38,9.基金项目
浙江省教育厅科研资助项目(Y202248528) （Y202248528）
湖州市科技计划资助项目(2023YZ28) （2023YZ28）
国家级大学生创新创业训练计划项目(202410347044) （202410347044）
浙江省大学生创新创业训练计划项目(S202410347087) （S202410347087）
