Table 4 Metric evaluation result after augmentation.
From: Minimal sourced and lightweight federated transfer learning models for skin cancer detection
Algorithm | Accuracy | Validation accuracy | Precision | Validation precision | Recall | Validation recall | Loss | Validation loss |
|---|---|---|---|---|---|---|---|---|
DenseNet201 | 26.64 | 32 | 86.57 | 51.98 | 8.06 | 13.11 | 2.02 | 2.58 |
EfficientNetB3 | 93.22 | 90.33 | 94.74 | 91.05 | 90.76 | 85.89 | 0.43 | 0.58 |
EfficientNetV2S | 51.63 | 58.67 | 74.8 | 65.76 | 29.47 | 51 | 1.58 | 2.6 |
MobileNetV2 | 49.17 | 41 | 73.4 | 42.72 | 26.29 | 35.89 | 1.62 | 7.82 |
VGG16 | 13.11 | 13.33 | 0 | 50 | 0 | 0.11 | 2.21 | 563.24 |
VITB16 | 66.65 | 80.33 | 76.51 | 82.87 | 56.58 | 76.89 | 0.92 | 0.51 |
