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

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Res2NetYOLACT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。

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.