Table 5.

Comparison of results achieved using various pre-trained networks in combination with proposed classifier. Best results achieved using multi-CNN is indicated in bold.

Network	Precision	Recall	F-measure	AUC	Accuracy
Squeezenet+Darknet-53+MobilenetV2+Xception+Shufflenet	0.853	0.985	0.914	0.963	91.1579
Darknet-53+MobilenetV2+Resnet-101+NasnetLarge+Xception	0.839	0.969	0.9	0.959	89.6842
Shufflenet+Darknet-53+Mobilenet+Resnet-101+NasnetLarge	0.826	0.974	0.894	0.952	88.9474
Resnet-101+NasnetLarge+Xception+VGG-19+Squeezenet	0.833	0.98	0.901	0.952	89.6842
Densenet-201+InceptionResnetV2+Shufflenet+Darknet-53+MobilenetV2	0.846	0.967	0.902	0.952	90
Densenet+InceptionResnetV2+Shufflenet+Darknet-53	0.837	0.951	0.89	0.944	88.8421
Squeezenet+Darknet-53+MobilenetV2+Xception	0.842	0.985	0.907	0.962	90.4211
Squeezenet+Darknet-53+Shufflenet+Xception	0.837	0.987	0.906	0.955	90.2105
InceptionResnetV2+Shufflenet+Darknet-53+MobilenetV2	0.846	0.969	0.903	0.951	90.1053
Squeezenet+Darknet-53+Shufflenet	0.815	0.971	0.886	0.943	88.1053
Squeezenet+Darknet-53+MobilenetV2	0.826	0.974	0.894	0.948	88.9474
Darknet+InceptionResnetV2+MobilenetV2	0.847	0.951	0.896	0.954	89.4737
Densenet-201+Darknet-53	0.815	0.98	0.89	0.931	88.4211
Darknet-53+InceptionResnetV2	0.84	0.929	0.883	0.94	88.2105
Squeezenet+Shufflenet	0.809	0.971	0.883	0.933	87.6842
Densenet-201	0.809	0.947	0.873	0.924	86.8421
Darknet-53	0.8	0.956	0.871	0.919	86.5263
InceptionResnetV2	0.806	0.96	0.876	0.918	87.0526
MobilenetV2	0.83	0.956	0.888	0.942	88.5263
NasnetLarge	0.819	0.936	0.873	0.906	87.0526
Resnet-101	0.814	0.958	0.88	0.925	87.5789
Shufflenet	0.813	0.971	0.885	0.925	88
Squeezenet	0.803	0.934	0.863	0.908	85.8947
VGG-19	0.816	0.949	0.878	0.914	87.3684
Xception	0.817	0.985	0.893	0.91	88.7368