Metaheuristic-based Deep COVID-19 Screening Model from Chest X-Ray Images

Table 3

Accuracy analysis among the proposed SPEA-II-based automated diagnosis model and the existing models.

Model name	Accuracy
CNN [16]	95.3%
MobileNetV2 and SqueezeNet [20]	98.25% and 97.81%
LBP [18]	99%
CNN [17]	97.4%
COVID-Net [19]	92.4%
CovXNet [22]	97.4% for binary and 89.6% for three classes
VGG19 [21]	98.75% for binary and 93.48% for multiclass cases
Xception and ResNet50_V2 [25]	91.4%
ResNet50 [23]	98%
DeTraC [27]	95.12%
Ensemble model [26]	96.4%
Truncated InceptionNet [28]	97.92%
Proposed model	99.13%