改进Res2Net-YOLACT模型的输电线路检测方法
Transmission line detection method based on improved Res2Net-YOLACT model
孙钱承 1丁云飞 1张杨天 1陈启凡 1田锟1
作者信息
- 1. 上海电机学院电气学院,上海 201306
- 折叠
摘要
为了提高电网无人机巡检中对输电线路目标检测效率,提出了一种改进的Res2Net-YOLACT输电线路检测方法.该方法采用以Res2Net为主干的YOLACT模型,快速准确地对输电线路进行特征提取.通过改进模型的非极大值抑制算法,提高模型的检测精度与速度.在真实公开数据集展开的实验结果表明,改进后的模型比改进前获得了更高的检测精度与速度,具有更好的输电线路检测性能.
Abstract
To improve the efficiency of transmission line target detection in unmanned aerial vehicle(UAV)inspections of power grids,an improved Res2Net-YOLACT transmission line detection method is proposed.The YOLACT model with Res2Net as the backbone is used to quickly and accurately extract features of transmission lines.Then,the detection accuracy and speed of the model are increased by improving the non-maximum suppression algorithm of the model.Experimental results based on a real public dataset show that the improved model achieves higher detection accuracy and better speed compared to the original model,and has better performance in transmission line detection.
关键词
无人机电力巡检/输电线路检测/非极大值抑制Key words
UAV electric power inspection/powerline detection/non-maximum suppression引用本文复制引用
基金项目
航空科学基金(20200001012015)
出版年
2024
NETL
NSTL
万方数据