Table 12 Fold − 2 Cross-validation performance of DAC-GAN with CKPF images.
Model | Accuracy (%) | Sensitivity (%) | Specificity (%) | Precision (%) | Recall (%) | F1-Score (%) | IoU (%) |
|---|---|---|---|---|---|---|---|
DenseNet121 | 78.42 | 76.57 | 79.23 | 76.98 | 76.57 | 76.77 | 60.48 |
VGG19 | 79.67 | 78.02 | 80.33 | 78.33 | 78.02 | 78.17 | 61.60 |
Inception | 80.48 | 78.74 | 81.20 | 79.23 | 78.74 | 78.98 | 63.24 |
XCeption | 81.54 | 79.58 | 82.33 | 80.24 | 79.58 | 79.91 | 64.33 |
MobileNet | 82.73 | 80.39 | 83.25 | 81.20 | 80.39 | 80.79 | 66.21 |
ResNet-50 | 83.95 | 81.41 | 84.72 | 82.15 | 81.41 | 81.78 | 67.96 |
EfficientNet-B0 | 85.64 | 83.22 | 86.34 | 84.09 | 83.22 | 83.65 | 70.17 |
EfficientNet-B4 | 87.38 | 84.87 | 88.11 | 85.72 | 84.87 | 85.29 | 72.55 |
ConvNeXt | 89.02 | 86.43 | 89.79 | 87.49 | 86.43 | 86.96 | 74.61 |
ViT CNN | 89.86 | 87.38 | 90.16 | 88.21 | 87.38 | 87.79 | 76.35 |
SwinT | 90.11 | 88.04 | 90.47 | 88.86 | 88.04 | 88.45 | 77.54 |
WGAN | 93.44 | 92.21 | 93.15 | 93.22 | 93.21 | 92.81 | 93.81 |
CGAN | 92.53 | 93.44 | 92.12 | 92.54 | 92.17 | 93.55 | 93.67 |
DAC-GAN | 99.81 | 99.86 | 99.91 | 99.84 | 99.86 | 99.85 | 99.65 |
