现代信息科技2024，Vol.8Issue(10)：13-16,4.DOI:10.19850/j.cnki.2096-4706.2024.10.003
基于YOLOv5改进的小目标检测算法研究
Research on Improved Small Target Detection Algorithm Based on YOLOv5
朱梦琳 1尹泉贺 1原素慧1
作者信息
- 1. 华北水利水电大学 信息工程学院,河南 郑州 450046
- 折叠
摘要
Abstract
To solve the problems of low accuracy and missed detection of small targets in scenarios by UAV,an improved small target detection algorithm DE_YOLOv5 based on YOLOv5 is proposed.The dataset of DE_YOLOv5 adopts VisDrone2019.The experiment includes two aspects.One is to introduce a decoupling joint mechanism,which reduces the impact of receptive field limitations on small target localization through independent center point prediction.mAP@0.5 of the initial model is 0.334,mAP@0.5 value is 0.344 after adding decoupling joint.The second is to replace the loss function with Focal-EIoU,and mAP@0.5 value is 0.351 after replacing the loss function.The experimental results show that DE_YOLOv5 can effectively improve the detection accuracy of small targets.关键词
小目标/解耦合头/图像识别Key words
small goal/decoupling joint/image recognition分类
信息技术与安全科学引用本文复制引用
朱梦琳,尹泉贺,原素慧..基于YOLOv5改进的小目标检测算法研究[J].现代信息科技,2024,8(10):13-16,4.
