1. YOLOv7-tiny Transmission Line Foreign Object Detection Algorithm Based on Channel Pruning.
- Author
-
SUN Yang and LI Jia
- Subjects
OBJECT recognition (Computer vision) ,FOREIGN bodies ,ELECTRIC lines ,ALGORITHMS ,LAMPS - 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 network is used to replace the backbone network of YOLOv7-tiny to address the feature bottleneck issue in the original network. 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. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF