| Training set | Testing set | mAP \(\text {IOU}_{\text {all}}\) | mAR100 \(\text {IOU}_{\text {all}}\) | F1 \(\text {IOU}_{\text {all}}\) | mAP \(\text {IOU}_{\text {0.5}}\) | mAR100 \(\text {IOU}_{\text {0.5}}\) | F1 \(\text {IOU}_{\text {0.5}}\) |
|---|
| T15U15 training | UGA2018 testing | 0.763 | 0.808 | 0.785 | 0.981 | 1.000 | 0.991 |
| UGA2018 training | UGA2018 testing | 0.778 | 0.818 | 0.798 | 0.983 | 0.992 | 0.987 |
| T15U18 training | UGA2015 testing | 0.179 | 0.335 | 0.233 | 0.352 | 0.683 | 0.464 |
| UGA2015 training | UGA2015 testing | 0.599 | 0.695 | 0.643 | 0.923 | 0.997 | 0.959 |
| U15U18 training | TAMU2015 testing | 0.377 | 0.535 | 0.442 | 0.588 | 0.857 | 0.698 |
| TAMU2015 training | TAMU2015 testing | 0.791 | 0.827 | 0.809 | 0.989 | 1.000 | 0.995 |
- For the testing set in each of the UGA2018, UGA2015, and TAMU2015 datasets, two Faster RCNN models were trained using the training set from the same dataset and from the combination of the other two datasets, respectively. Performance comparison of the two models was used to evaluate the model generalizability
