Prediction of COVID-19 using Convolution Neural Network - Prathibhavani P. M. - Bog

Convolutional Neural Networks (CNN) and Machine Learning (ML) have evolved a long way in the modern technological era. They are used in analysis and prediction of various segments of normal life. They have a greater advantage when it comes to understanding a process, sometimes even better than a human brain. The Virus that is generated as COVID-19 is mainly caused when a person coughs, sneeze or exhales and it is transmitted as a small particle to other bodies and form these viruses. One of the major tricks for stopping the spread of this covid-19 is social distancing and rapid testing. This rapid test will take 2-3 days of time to get the result of covid-19. This may trouble a large amount of people in terms of money and time. Therefore, with the advantage of CNN, devised a method to increase the efficiency of the testing process. X-rays and CT scans show considerable advantage in detecting COVID-19 in a person. COVID-19 affects the lungs primarily which could be caught in X-rays as a white overlay. Constructed a model that could identify whether the submitted X-ray is of a normal person or of a COVID-19 positive person.