Table 7 Performance Comparison of Different Classifiers on HAM10000 dataset.
Classifier | Accuracy (%) | Precision (%) | Recall (%) | F1-Score (%) | AUC | Model Size (MB) | Inference (ms) |
|---|---|---|---|---|---|---|---|
VGG-16 | 91.12 | 92.09 | 90.43 | 91.13 | 99.02 | 33.6 | 28.1 |
VGG-19 | 91.68 | 92.23 | 90.57 | 91.71 | 98.14 | 39.6 | 32.7 |
Enhanced VGG-19 | 92.51 | 92.95 | 91.40 | 92.17 | 98.75 | 43.1 | 36.2 |
ResNet-152 | 89.32 | 90.73 | 88.21 | 89.27 | 98.74 | 230.0 | 45.5 |
EfficientNet-B0 | 89.46 | 90.21 | 88.21 | 89.31 | 98.43 | 16.5 | 23.2 |
Inception-V3 | 91.82 | 92.28 | 91.12 | 91.76 | 99.06 | 92.1 | 27.4 |
MobileNetV3 | 91.97 | 92.13 | 90.51 | 91.78 | 98.95 | 3.7 | 11.3 |
ShuffleNet | 90.43 | 90.89 | 89.76 | 90.23 | 98.41 | 2.5 | 9.7 |
Swin Transf. | 95.33 | 95.14 | 94.62 | 94.87 | 99.11 | 89.7 | 27.2 |
ConvNeXt | 94.56 | 94.81 | 94.09 | 94.45 | 99.05 | 87.2 | 28.4 |
DSSCC-Net | 98.00 | 97.00 | 97.00 | 97.00 | 99.43 | 3.42 | 12.6 |
