Trained and validated on Sheep No. | No. of patterns in the train dataset | Tested on Sheep No. | No. of patterns in the Test-set | TP hits | TN hits | FP hits | FN hits | Sensitivity [%] | Selectivity [%] | Precision [%] | Accuracy [%] |
2,3,4,5,6,7 | 4567 | 1 | 443 | 148 | 270 | 25 | 0 | 100 | 85.5 | 100 | 94.4 |
1,3,4,5,6,7 | 4751 | 2 | 259 | 108 | 149 | 2 | 0 | 100 | 98.2 | 100 | 99.2 |
1,2,4,5,6,7 | 4731 | 3 | 279 | 82 | 192 | 1 | 4 | 95.3 | 98.8 | 98.0 | 98.2 |
1,2,3,5,6,7 | 3372 | 4 | 1638 | 818 | 795 | 6 | 19 | 97.7 | 99.3 | 97.7 | 98.5 |
1,2,3,4,6,7 | 4088 | 5 | 922 | 454 | 455 | 13 | 0 | 100 | 97.2 | 100 | 98.6 |
1,2,3,4,5,7 | 4466 | 6 | 544 | 231 | 305 | 0 | 8 | 96.7 | 100 | 97.4 | 98.5 |
1,2,3,4,5,6 | 4085 | 7 | 925 | 209 | 702 | 2 | 14 | 93.7 | 99.0 | 98.0 | 98.3 |
Overall performance of the 5 layers WF-CNN in the entire 6 hours | 97.96±1.48 |