Table 11 Performance analysis of fold-4 cross-validation.
From: Feature fusion context attention gate UNet for detection of polycystic ovary syndrome
Model | Accuracy | Precision | Recall | Specificity | F1-Score |
|---|---|---|---|---|---|
DenseNet | 69.6 | 69.2 | 68.7 | 70.2 | 68.9 |
VGG | 72.9 | 72.4 | 72.2 | 73.4 | 72.3 |
AlexNet | 74.0 | 73.7 | 73.3 | 74.4 | 73.5 |
ResNet | 77.6 | 77.2 | 76.9 | 78.1 | 77.1 |
U-Net | 79.6 | 79.2 | 78.9 | 80.0 | 79.0 |
Attention U-Net | 83.7 | 83.4 | 83.0 | 84.2 | 83.2 |
FCAU-Net | 99.9 | 99.9 | 99.8 | 99.9 | 99.9 |
