A Hybrid Model for Covid-19 Detection using CT-Scans

Although some believe it has been wiped out, the coronavirus is striking again. Controlling this epidemic necessitates early detection of disease. Computed tomography (CT) scan images allow fast and accurate screening for COVID-19. This study seeks to develop most precise model identifying classifying COVID-19 by developing an automated approach using transfer-learning CNN models as a base. Transfer learning like VGG16, Resnet50, Xception are employed in study. The VGG16 98.39% accuracy, Resnet50 97.27% 96.6% accuracy; after that, hybrid made stacking ensemble method accuracy 98.71%. According findings, architecture offers greater than single architecture.