COVID-19 Detection Through Deep learning and Comparitive analysis of different models

As covid-19 has grown a lot and have become the biggest problem of recent times. Our whole world is still suffering from this disease. This disease has taken life of lot of people therefore is the biggest curse of all time and hence we need a system which can detect this disease. The system proposed in this paper makes it easy to detect COVID-19 using deep learning models. This paper presents a comparative analysis of different models developed for COVID-19 detection. Three models were created with following architecture Resnet50, Xception and VGG16 with the accuracy rate of 98.01%, 93.04% and 95.77% respectively. Our system results have shown that the Resnet50 model is most accurate hence it can detect the disease accurately.