Table 10.

Performance comparison of the COVID-19/normal classification in this study according to the literature

Class	Subjects	Method	Prec (%)	Sens. (%) or recall	f1- score	Acc (%)	Ref
COVID- 19/normal	Dataset 2	DenseNet-201	96.29	96.29	96.29	96.25	Jaiswal et al. [12]
COVID- 19/normal	Dataset 2	VGG19	94.86	94.04	–-	95.0	Panwar et al. [24]
COVID- 19/normal	Dataset 1	CNN	93.0	95.0	–-	78.5	Wu et al. [26]
COVID- 19/normal	Dataset 1	DenseNet-169	–-	–-	0.85	0.86	He et al. [25]
COVID- 19/normal	Dataset1:698 349 COVID,349 Non-COVID Dataset2:2260 1230 COVID,1230 Non-COVID	MobileNetv2, ResNet50 and Deep Features	98.18	98.09	98.12	98.12	Proposed Approach (MobilNetv2 + SVM)
			95.83	95.75	95.77	95.79	Proposed Approach (MobilNetv2 + kNN)
			99.05	99.06	99.06	99.06	Proposed Approach (ResNet-50 + SVM)
			99.38	99.36	99.37	99.37	Proposed Approach (ResNet-50 + kNN)