Deep Convolutional Neural Network Approach for COVID-19 Detection

Coronavirus disease 2019 (Covid-19) is a life-threatening infectious caused by newly discovered strain of the coronaviruses. As end 2020, Covid-19 still not fully understood, but like other similar viruses, main mode transmission or spread believed to be through droplets from coughs and sneezes infected persons. The accurate detection cases poses some questions scientists physicians. two kinds tests available for are viral tests, which tells you whether currently antibody test, if had been previously. Routine test can take up 2 days complete; in reducing chances false negative results, serial testing used. Medical image processing means using Chest X-ray images Computed Tomography (CT) help radiologists detect virus. This imaging approach certain characteristic changes lung associated with Covid-19. In this paper, deep learning model technique based on Convolutional Neural Network proposed improve accuracy precisely Xray scans identifying structural abnormalities images. entire categorized into three stages: dataset, data pre-processing final stage being training classification.