Paper Title
PROCESSING OF CHEST X-RAY METAPHORS TO PERCEIVE THE SEVERITY OF COVID 19 CONTAGIONS USING DEEP LEARNING PROCEDURES

Abstract
Abstract - The contribution of Artificial Intelligence to the medical field in diagnosing various ailments have been triggered in the recent years and one such impact is the exposure of corona virus in the most reliable manner. Recently the familiar infection COVID 19 caused by coronavirus was first discovered in Wuhan in the end of the year which became major disaster for this century. The disease spread rapidly without control and the only remedy was preventive measures taken in advance. The examination depended on chest x-ray images which were processed to differentiate from pneumonia and other cold related diseases. This paper is related to the images identified as corona virus and the sternness of the disease is categorized into three classes. The images are segmented and classified using various deep learning techniques like Residual network, Exception model and Dense net model for comparison purposes. The best model is chosen from the accuracy produced with the given data sets. The deep learning Xception model proves to be the best with overall accuracy of 89% in identifying the disease using the chest x-ray images. Keywords - Artificial Intelligence, Corona Virus, COVID 19, X-Ray Images, Pneumonia, Deep Learning Techniques, Residual Network, Exception Model, Dense Net Model.