Table 5.
Performance comparison of deep features and deep features selected by ReliefF algorithm. Performances in the left column are all deep features, performances in the right column are selected deep features by ReliefF.
(Acc, accuracy, Rec, recall, Spe, specificity, Pre, precision, F1, F1-score).
| Methods/Algorithm | Performances(%) for all features |
Performances(%) for selected features |
||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Acc | Rec | Spe | Pre | F1 | Acc | Rec | Spe | Pre | F1 | |
| MobileNet/SVM Linear | 82.5 | 85.6 | 79.3 | 80.5 | 83.0 | 85.0 | 88.2 | 81.8 | 82.9 | 85.4 |
| MobileNet/SVM Quadratic | 80.6 | 84.0 | 77.3 | 78.6 | 81.2 | 86.0 | 89.4 | 82.7 | 83.7 | 86.4 |
| MobileNet/SVM Cubic |
80.1 |
84.0 |
76.3 |
77.9 |
80.8 |
87.3 |
89.9 |
84.7 |
85.4 |
87.6 |
| ResNet50/SVM Linear | 78.3 | 81.6 | 75.1 | 76.5 | 79.0 | 85.2 | 87.2 | 83.2 | 83.8 | 85.4 |
| ResNet50/SVM Quadratic | 86.1 | 88.2 | 84.0 | 84.6 | 86.4 | 97.4 | 97.6 | 97.1 | 97.2 | 97.5 |
| ResNet50/SVM Cubic | 84.0 | 86.1 | 81.9 | 82.5 | 84.3 | 97.8 | 98.5 | 97.3 | 97.4 | 98.0 |