Table 6 Evaluation metrics for the LBC dataset (4-class).
Iteration | Algorithm | Precision (%) | Sensitivity (%) | Accuracy (%) | MCC | F-Score |
|---|---|---|---|---|---|---|
Iteration-1 | ResNet-152 | 93.33 | 97.3 | 97.94 | 0.96 | 0.95 |
VGG-16 | 98.13 | 97.6 | 98.97 | 0.98 | 0.98 | |
Proposed method | 98.33 | 99.27 | 99.48 | 0.99 | 0.99 | |
Iteration-2 | ResNet-152 | 95 | 97.92 | 98.45 | 0.97 | 0.96 |
VGG-16 | 98.33 | 99.27 | 99.48 | 0.99 | 0.99 | |
Proposed method | 100 | 100 | 100 | 1.00 | 1.00 | |
Iteration-3 | ResNet-152 | 96.67 | 98.57 | 98.97 | 0.98 | 0.98 |
VGG-16 | 98.33 | 99.27 | 99.48 | 0.99 | 0.99 | |
Proposed method | 100 | 100 | 100 | 1.00 | 1.00 |
