Table 4.
Classification results of DarkNet53 using ultrasound images, where the training/testing ratio is 60:40.
| Classifier | Sensitivity (%) | Precision (%) | F1 Score (%) | Accuracy (%) | FNR (%) | Classification Time (s) |
|---|---|---|---|---|---|---|
| CSVM | 98.9 | 98.9 | 98.9 | 98.9 | 1.1 | 107.697 |
| MGSVM | 98.7 | 98.7 | 98.7 | 98.7 | 1.3 | 103.149 |
| QSVM | 98.7 | 98.7 | 98.7 | 98.7 | 1.3 | 89.049 |
| ESD | 98.6 | 98.7 | 98.65 | 98.7 | 1.4 | 94.31 |
| LSVM | 98.5 | 98.5 | 98.5 | 98.6 | 1.5 | 68.827 |
| ESKNN | 97.9 | 98 | 97.95 | 98.0 | 2.1 | 79.34 |
| FKNN | 97.8 | 97.8 | 98.24 | 97.8 | 2.2 | 84.537 |
| LD | 98.1 | 98.1 | 98.1 | 98.1 | 1.9 | 85.317 |
| CGSVM | 97.8 | 97.9 | 98.34 | 97.9 | 2.2 | 76.2 |
| WKNN | 97.2 | 97.2 | 97.2 | 97.2 | 2.8 | 81.191 |