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 5 常见目标检测模型的性能对比

Tab.5 Performance comparison of common object detection models

模型 P/% R/% Par/MB Me/MB FPS mAP_0.5/% Faster R-CNN 71.51 85.61 137.10 522.99 13.18 87.88 YOLOv3 93.63 87.39 61.53 234.74 39.63 92.11 YOLOv4 93.82 91.22 63.95 243.94 30.97 93.97 YOLOX-s 97.74 97.21 8.94 34.10 42.89 97.15 YOLOv7 96.75 94.97 37.21 141.93 33.14 97.03 YOLOv5s 96.59 94.08 7.03 26.81 50.39 96.37 SG-YOLOv5s 96.80 97.96 2.02 7.70 47.39 97.63