Table 4 Comparative outcome of CADHDD-SFLNHM approach with other methods.
Model | Accuy | Recal | F1Score | GMean |
|---|---|---|---|---|
SRGAN-EfficientNetB7 | 89.97 | 92.71 | 90.69 | 86.06 |
CNN-Inception V3 | 85.41 | 88.85 | 89.70 | 89.58 |
CNN-ResNet50 | 74.58 | 81.00 | 74.00 | 73.00 |
GoogleNet Model | 90.86 | 86.39 | 89.33 | 89.61 |
RCNN Classifier | 86.82 | 86.44 | 92.58 | 91.17 |
MobileNetV2 Model | 78.47 | 78.00 | 78.00 | 78.00 |
InceptionV3 Method | 97.20 | 92.58 | 93.23 | 93.88 |
VGG16 Algorithm | 96.09 | 91.11 | 92.60 | 92.39 |
CADHDD-SFLNHM | 97.91 | 95.81 | 95.86 | 95.83 |
