Table 5.

Illustrates the performance of the proposed model compared to existing pre-trained state-of-the-art architectures.

Models	Accuracy	Sensitivity	Specificity	AUC-ROC	F1-score
VGG16	0.9603	0.9567	0.9640	0.9920	0.9560
VGG19	0.9597	0.9560	0.9632	0.9910	0.9550
Inception V3	0.9280	0.9250	0.9302	0.9760	0.9251
ResNet50 V2	0.9390	0.9356	0.9408	0.9410	0.9820
Xception	0.9470	0.9420	0.9480	0.9792	0.9439
DenseNet121	0.9562	0.9482	0.9650	0.9901	0.9480
MobileNetV2	0.9483	0.9420	0.9552	0.9880	0.9478
Capsule net	0.9518	0.9500	0.9514	0.9900	0.9498
Proposed	0.9935	0.9957	0.9912	0.9973	0.9936