ABSTRACT
The coronavirus pandemic brought the world to a standstill of historic significance. Countries over the world have imposed lockdowns, quarantines and travel bans in an effort to stop the further spread of the disease. Healthcare systems worldwide are under extreme pressure due to the influx of a large amount of patients suffering from COVID-19. Moreover, there is a dearth of doctors, nurses, and support staff in hospitals of many countries. In such a predicament, it is imperative to leverage the advances made in computer vision and deep learning technologies to create a system that attempts to ease the burden on worldwide healthcare. In this research, ten state-of-the-art pre-trained convolutional neural networks were used to identify COVID-19 in chest Computed Tomography (CT) scan images. After extensive experimental testing and tuning, comprehensive comparative analysis was done and very promising results were obtained in this classification task. © 2021 IEEE