Table 1 Results obtained by CNN models30.
From: Utilizing convolutional neural networks to classify monkeypox skin lesions
Models | Accuracy | Sensitivity | Specificity | F1 Score | Training time | Size of model weight file |
|---|---|---|---|---|---|---|
ResNet-18 | 98.25% | 96.55% | 100.00% | 98.25% | 3 min 32 s | 42.7 Megabyte |
ResNet-50 | 96.49% | 93.10% | 100.00% | 96.43% | 4 min 33 s | 90.0 Megabyte |
VGG-16 | 92.98% | 89.66% | 96.43% | 92.86% | 5 min 39 s | 512 Megabyte |
Densenet-161 | 96.49% | 96.55% | 96.43% | 96.55% | 6 min 52 s | 102 Megabyte |
EfficientNet B7 | 94.74% | 100.00% | 89.29% | 95.08% | 8 min 27 s | 245 Megabyte |
EfficientNet V2 | 96.49% | 100.00% | 92.86% | 96.67% | 8 min 57 s | 449 Megabyte |
GoogLeNet | 96.49% | 96.55% | 96.43% | 96.55% | 5 min 35 s | 512 Megabyte |
MobileNet V2 | 98.25% | 96.55% | 100.00% | 98.25% | 3 min 42 s | 8.75 Megabyte |
MobileNet V3 | 75.44% | 62.07% | 89.29% | 72.00% | 3 min 10 s | 5.94 Megabyte |
ResNeXt-50 | 92.98% | 100.00% | 85.71% | 93.55% | 5 min 15 s | 88.0 Megabyte |
ShuffleNet V2 | 78.95% | 65.52% | 92.86% | 76.00% | 3 min 37 s | 20.6 Megabyte |
ConvNeXt | 96.49% | 100.00% | 92.86% | 96.67% | 23 min 25 s | 748 Megabyte |
