计算机工程与应用2024，Vol.60Issue(14)：319-328,10.DOI:10.3778/j.issn.1002-8331.2311-0160
基于通道剪枝的YOLOv7-tiny输电线路异物检测算法
YOLOv7-tiny Transmission Line Foreign Object Detection Algorithm Based on Channel Pruning
孙阳 1李佳1
作者信息
- 1. 吉林化工学院信息与控制工程学院,吉林 132022
- 折叠
摘要
Abstract
In response to the problem of poor accuracy and the large model size in transmission line foreign object detection,an improved YOLOv7-tiny algorithm based on channel pruning has been proposed.Firstly,the ReXNet net-work is used to replace the backbone network of YOLOv7-tiny to address the feature bottleneck issue in the original net-work.Secondly,diversified branch blocks are introduced to enhance the network's feature fusion capability.Finally,through layer-adaptive magnitude-based pruning(LAMP),a pruning approach is employed to trade off some accuracy for a reduction in model size and computational load,preparing it for deployment on embedded devices.Experimental results indicate that the final improved model achieves a 3 percentage points increase in accuracy compared to the YOLOv7-tiny model,a 119.4％increase in FPS,and compresses the model size to 14％of the original size.关键词
输电线路/YOLOv7-tiny算法/通道剪枝/异物检测Key words
transmission lines/YOLOv7-tiny algorithm/channel pruning/foreign object detection分类
信息技术与安全科学引用本文复制引用
孙阳,李佳..基于通道剪枝的YOLOv7-tiny输电线路异物检测算法[J].计算机工程与应用,2024,60(14):319-328,10.
