Table 2.

Results for COVID-19 classification using CT images

Model	Accuracy	Type	Precision	Recall	F1-score
Xception [45]	0.98	Macro	0.97	0.98	0.97
		Weighted	0.98	0.98	0.98
VGG16 [21]	0.68	Macro	0.34	0.50	0.40
		Weighted	0.46	0.68	0.54
VGG19 [40]	0.83	Macro	0.81	0.85	0.82
		Weighted	0.86	0.83	0.83
ResNet50 [46]	0.86	Macro	0.84	0.87	0.85
		Weighted	0.88	0.86	0.86
ResNet101 [47]	0.86	Macro	0.84	0.88	0.85
		Weighted	0.88	0.86	0.86
InceptionV3 [33]	0.95	Macro	0.95	0.94	0.94
		Weighted	0.95	0.95	0.95
InceptionResNetV2 [47]	0.96	Macro	0.96	0.95	0.96
		Weighted	0.96	0.96	0.96
MobileNetV2 [47]	0.71	Macro	0.75	0.78	0.71
		Weighted	0.83	0.71	0.72
DenseNet121 [36]	0.89	Macro	0.91	0.84	0.87
		Weighted	0.90	0.89	0.89
DenseNet201 [47]	0.89	Macro	0.91	0.84	0.87
		Weighted	0.90	0.89	0.89
NASNetMobile [47]	0.68	Macro	0.34	0.50	0.40
		Weighted	0.46	0.68	0.54
NASNetLarge [47]	0.68	Macro	0.34	0.50	0.40
		Weighted	0.46	0.68	0.54
ResNet152	0.76	Macro	0.85	0.64	0.64
		Weighted	0.81	0.76	0.71
ResNet50V2	0.90	Macro	0.88	0.92	0.89
		Weighted	0.92	0.90	0.90
ResNet101V2	0.80	Macro	0.88	0.69	0.71
		Weighted	0.84	0.80	0.77
ResNet152V2	0.80	Macro	0.88	0.70	0.72
		Weighted	0.84	0.80	0.78
MobileNet	0.96	Macro	0.95	0.96	0.96
		Weighted	0.96	0.96	0.96
DenseNet169	0.94	Macro	0.95	0.91	0.92
		Weighted	0.94	0.94	0.93
EfficientNetB0	0.98	Macro	0.97	0.98	0.97
		Weighted	0.98	0.98	0.98
EfficientNetB1	0.96	Macro	0.97	0.94	0.95
		Weighted	0.96	0.96	0.96
EfficientNetB2	0.98	Macro	0.98	0.97	0.97
		Weighted	0.98	0.98	0.98
EfficientNetB3	0.97	Macro	0.95	0.97	0.96
		Weighted	0.97	0.97	0.97
EfficientNetB4	0.96	Macro	0.95	0.97	0.96
		Weighted	0.96	0.96	0.96
EfficientNetB5	0.98	Macro	0.98	0.97	0.97
		Weighted	0.98	0.98	0.98
EfficientNetB6	0.97	Macro	0.97	0.96	0.96
		Weighted	0.97	0.97	0.97
EfficientNetB7	0.97	Macro	0.96	0.96	0.96
		Weighted	0.97	0.97	0.97
Proposed	0.99	Macro	0.99	0.99	0.99
		Weighted	0.99	0.99	0.99