摘要
在输电线路的缺陷检测中,鸟巢以及塑料、碎布等挂空悬浮物多为小目标。其所占像素少,容易被背景干扰,检测精度有待提高。设计了一种全新的两阶段目标检测算法,用于改善对输电线路中鸟巢以及挂空悬浮物的检测效果。为了提高小目标检测的性能,在特征提取模块中融入注意力机制,以学习更为丰富的上下文信息。此外,在检测模块中,设计了基于更为柔和非极大值抑制算法的后处理方法,以减少小目标的丢失。与常用的两阶段目标检测算法相比,该方法在两个类别的平均准确率上分别提高了约4.7%和5.9%,有着更高的实际应用价值。
In the defect detection of transmission lines,the bird's nest,plastic,rags and other suspended solids are mostly small targets.They have few pixels in the images and are easy to be disturbed by the background,which make the detection accuracy needs to be improved.In this paper,a new two-stage object detection algorithm is designed to improve the detection effect of bird nests and suspended solids in transmission lines.In order to improve the detection performance of small targets,the attention mechanism is integrated into the feature extraction network to learn more rich context information.In addition,in the detection network,a post-processing method based on softer non maximum suppression algorithm is designed to reduce the loss of small targets.Compared with the commonly used two-stage object detection algorithms,the proposed method improves the average accuracy of the two categories by about 4.7%and 5.9%,respectively,and has greater value in practical applications.
作者
赵云龙
田生祥
李岩
罗龙
齐鹏文
ZHAO Yunlong;TIAN Shengxiang;LI Yan;LUO Long;a QI Pengwen(State Grid Qinghai Electric Power Company Overhauling Company,Xining 810000)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2023年第6期906-914,共9页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金青年项目(61903155)
国网青海省电力公司双创孵化培育基金(106000004505)。
作者简介
通信作者:赵云龙(1988–),男,高级工程师,主要从事图像处理方面的研究,E-mail:rensheng202201@163.com。
