Abstract: Early diagnosis of the corona virus disease in 2019(COVID-19) is essential for controlling this pandemic. COVID-19 has been circulating rapidly all over the world. There is no vaccine· accessible for this virus yet. Fast and detailed COVID-19 screening is possible using computed tomography (CT) scan images. The deep learning techniques used in the proposed method is based on a complexity neural network (CNN).We immediate on differentiating the CT scan images of COVID-19 and non-COVID 19 CT using different deep learning techniques. A self-developed model named CTnet-10 was designed for the COVID-19diagnosis, having an accuracy of 82.1%. The VGG-19 proved to be superior with an accuracy of 94.52% as analyse to all other deep learning models. Automatic diagnosis of COVID-19 from the CT scan pictures can be used by the doctors as a brisk and competent method for COVID-19 screening.

Keywords: COVID-19, CNN, CT scan, diagnosis, VGG, CTnet-10.

| DOI: 10.17148/IARJSET.2022.9534