A new modification CNN using VGG19 and ResNet50V2 for classification of COVID-19 from X-ray radiograph images

Coronavirus often called COVID-19 is a deadly viral disease that causes as result of severe acute respiratory syndrome coronavirus-2 needs to be identified especially at its early stages, and failure which can lead the further spread virus. Despite with huge success recorded towards use original convolutional neural networks (CNN) deep learning models. However, their architecture modified design versions have more powerful feature layer extractors improve classification performance. This research aimed designing CNN model applied interpret X-rays classify cases improved Therefore, we proposed network (shortened modification CNN) approach uses case by combining VGG19 ResNet50V2 along putting additional dense layers combined extractors. The achieved 99.24%, 98.89%, 98.90%, 99.58%, 99.23% overall accuracy, precision, specificity, sensitivity, F1-Score, respectively. demonstrates results show promising performance in cases.