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 | 145 | 266 | 4 | 28 | 83.8 | 98.5 | 97.3 | 92.8 |
1,3,4,5,6,7 | 4751 | 2 | 259 | 108 | 148 | 1 | 2 | 98.2 | 99.3 | 99.1 | 98.8 |
1,2,4,5,6,7 | 4731 | 3 | 279 | 82 | 195 | 1 | 1 | 98.8 | 99.5 | 98.8 | 99.3 |
1,2,3,5,6,7 | 3372 | 4 | 1638 | 817 | 793 | 21 | 7 | 99.2 | 97.4 | 97.5 | 98.3 |
1,2,3,4,6,7 | 4088 | 5 | 922 | 454 | 392 | 60 | 13 | 97.2 | 86.6 | 88.3 | 92.1 |
1,2,3,4,5,7 | 4466 | 6 | 544 | 231 | 299 | 14 | 0 | 100 | 95.5 | 94.3 | 97.4 |
1,2,3,4,5,6 | 4085 | 7 | 925 | 208 | 709 | 7 | 1 | 99.5 | 99.0 | 96.7 | 99.1 |
Overall performance of the 7 layers 1D-CNN in the entire 6 hours | 96.83±2.83 |