TABLE 3.
[The mean average precision (mAP) of trained models on each image datasets using YOLOv5 and Faster RCNN. Red highlights indicate highest values within the model, as well as highlighting that YOLOv5 NIR has a higher mAP value than any Faster RCNN image type.]
| Model | Inference time, ms (1/FPS) | Image Type | mAP.5:.95 |
|---|---|---|---|
| YOLOv5 | 19.5 ms (1/51.28 FPS) |
Dual | 0.947 |
| RGB | 0.842 | ||
| NIR | 0.913 | ||
| Faster RCNN | 71.4 ms (1/13.99 FPS) |
Dual | 0.898 |
| RGB | 0.742 | ||
| NIR | 0.856 |