Research Article
Real-Time Object Detection for the Running Train Based on the Improved YOLO V4 Neural Network
Table 3
Comparison of AP values of different network models for four types of objects.
| Detection algorithm | Track (%) | Signal (%) | Tunnel (%) | Train (%) |
| Faster R–CNN | 97.82 | 84.87 | 85.68 | 91.73 | SSD | 96.59 | 73.62 | 74.60 | 92.01 | YOLO V3 | 97.32 | 86.37 | 87.41 | 92.05 | YOLO V4 | 97.99 | 89.78 | 89.03 | 92.77 | YOLO V4-tiny | 97.58 | 86.34 | 87.29 | 90.16 |
| MYOLO-lite series | MV1-YOLO-lite | 99.99 | 92.92 | 97.28 | 92.29 | MV2-YOLO-lite | 99.41 | 87.87 | 93.73 | 95.68 | MV3-YOLO-lite | 99.81 | 91.59 | 96.26 | 95.30 |
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