Real-Time Application for Covid-19 Class Detection based CNN Architecture

Abstract

Covid-19 disease has been known as a spreaded epidemic across the whole world that affects millions of people, causing deaths and catastrophic effects. For this reason, Computer Aided Diagnosis System (CAD), consists to be a crucial step using deep learning algorithms. In this context, a CNN network has been proposed using two optimizers networks such as Rmsprop and SGD with momentum.the whole system is implemented on both CPU and GPU with the aim to speed up the implementation time process. Then to have a medical real application which automatically detect the covid-19 class from X-rays images of chest. Classification results achieved in terms of accuracy, specificity and sensitivity 99.22%, 99.65% and 99.45% respectively, outperforming the state of the art. As a result, a medical real time application is achieved for Covid-19 class detection in a short time process.