Table 9. Performance analysis (COVID-19 image data).

The bold text with the value indicates better performance, characterized by higher accuracy and lower loss.

Model	Total parameter	Train accuracy	Train loss	Validation accuracy	Validation loss
CNN	9,014,660	0.9761	0.0367	0.9400	0.09550
VGG16	138,357,544	0.9768	0.0467	0.9420	0.09440
ResNet	25,636,712	0.7532	0.3064	0.7987	0.2749
InceptionNetV3	23,851,784	0.9707	0.0404	0.6175	0.1074
DenseNet121	8,062,504	0.8101	0.2739	0.6175	0.3904
XceptionNet	22,910,480	0.86623	0.1756	0.8800	0.1645
AlexNet	62,300,000	0.8968	0.1264	0.8737	0.1613
CNN-RNN	N/A	0.8663	0.2715	0.8150	0.3245
EfficientNetB2	9,177,569	0.9707	0.0904	0.2475	5.5966
MobileNetV2	3,538,984	0.9797	0.0402	0.6713	0.6609
VGG-19	143,667,240	0.9820	0.0461	0.9410	0.0951
MobileNet-V3	5,481,752	0.9811	0.0401	0.6712	0.6601