Table 11 Fold 1- Cross-validation performance of DAC-GAN with CKPF images.
Model | Accuracy (%) | Sensitivity (%) | Specificity (%) | Precision (%) | Recall (%) | F1-Score (%) | IoU (%) |
|---|---|---|---|---|---|---|---|
DenseNet121 | 78.31 | 76.42 | 79.10 | 76.81 | 76.42 | 76.61 | 60.32 |
VGG19 | 79.56 | 77.90 | 80.20 | 78.23 | 77.90 | 78.06 | 61.47 |
Inception | 80.35 | 78.61 | 81.04 | 79.10 | 78.61 | 78.85 | 63.15 |
XCeption | 81.39 | 79.47 | 82.16 | 80.12 | 79.47 | 79.79 | 64.22 |
MobileNet | 82.67 | 80.32 | 83.18 | 81.14 | 80.32 | 80.73 | 66.12 |
ResNet-50 | 83.82 | 81.25 | 84.64 | 82.07 | 81.25 | 81.66 | 67.83 |
EfficientNet-B0 | 85.48 | 83.04 | 86.22 | 83.91 | 83.04 | 83.47 | 70.08 |
EfficientNet-B4 | 87.26 | 84.72 | 87.93 | 85.58 | 84.72 | 85.10 | 72.44 |
ConvNeXt | 88.92 | 86.24 | 89.65 | 87.33 | 86.24 | 86.78 | 74.38 |
ViT CNN | 89.75 | 87.19 | 90.08 | 88.06 | 87.19 | 87.62 | 76.22 |
SwinT | 90.00 | 87.85 | 90.36 | 88.72 | 87.85 | 88.28 | 77.43 |
WGAN | 93.88 | 92.81 | 93.10 | 92.11 | 92.82 | 92.89 | 92.45 |
CGAN | 92.54 | 93.55 | 91.95 | 93.23 | 91.13 | 91.52 | 91.55 |
DAC-GAN | 99.78 | 99.84 | 99.89 | 99.80 | 99.84 | 99.82 | 99.60 |
