Table 5.

Experimental results of different models on the same dataset for COVID-19 vs Normal classification.

CNN Models	Accuracy	Precision	Recall	Specificity	F1-score	Confusion Matrix
CheXNet	99.21%	98.52%	100%	98.35%	99.25%	358 6
						0 399
Resnet50	99.34%	98.76%	100%	98.63%	99.38%	359 5
						0 399
VGG-19	99.61%	99.25%	100%	99.18%	99.63%	361 3
						0 399
MobileNetV2	99.61%	99.25%	100%	99.17%	99.62%	361 3
						0 399
VGG-16	99.74%	99.75%	99.74%	99.73%	99.74%	363 1
						1 398
EfficientNet	99.74%	99.50%	100%	99.45%	99.75%	362 2
						0 399
Proposed Model	99.87%	99.75%	100%	99.73%	99.87%	363 1
						0 399