轻量化YOLOv5s网络车底危险物识别算法
金鑫,庄建军,徐子恒

Lightweight YOLOv5s network-based algorithm for identifying hazardous objects under vehicles
Xin JIN,Jian-jun ZHUANG,Zi-heng XU
表 1 Backbone网络结构参数
Tab.1 Structure parameters of Backbone network
序号 模块重复次数 模块名 参数配置 输出大小
0 1 Focus [3, 32, 3] 32×320×320
1 1 S-(2) [32, 64, 2] 64×160×160
2 1 S-(1) [64, 64, 1] 64×160×160
3 1 S-(2) [64, 128, 2] 128×80×80
4 3 S-(1) [128, 128, 1] 128×80×80
5 1 S-(2) [128, 256, 2] 256×40×40
6 3 S-(1) [256, 256, 1] 256×40×40
7 1 S-(2) [256, 512, 2] 512×20×20
8 1 SPPF [512, 512, [5, 5, 5]] 512×20×20
9 1 S-(1) [512, 512, 1] 512×20×20