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 | 118 | 270 | 0 | 55 | 68.2 | 100 | 100 | 87.6 |
1,3,4,5,6,7 | 4751 | 2 | 259 | 106 | 149 | 0 | 4 | 96.4 | 100 | 100 | 98.5 |
1,2,4,5,6,7 | 4731 | 3 | 279 | 79 | 191 | 5 | 4 | 95.2 | 97.4 | 94.0 | 96.8 |
1,2,3,5,6,7 | 3372 | 4 | 1638 | 728 | 814 | 0 | 96 | 88.3 | 100 | 100 | 94.1 |
1,2,3,4,6,7 | 4088 | 5 | 922 | 431 | 455 | 0 | 36 | 92.3 | 100 | 100 | 96.1 |
1,2,3,4,5,7 | 4466 | 6 | 544 | 228 | 311 | 2 | 3 | 98.7 | 99.4 | 99.1 | 99.1 |
1,2,3,4,5,6 | 4085 | 7 | 925 | 203 | 711 | 5 | 6 | 97.1 | 99.3 | 97.6 | 98.8 |
Overall performance of the 5 layers 1D-CNN in the entire 6 hours | 95.86±3.74 |