Predicting COVID-19 from chest X-ray images using fine tuning and transfer learning

Abstract

Transfer learning is the act of transferring pre-existing knowledge to another model to solve similar problem, due to the recent world pandamic caused by the newly discovered COVID-19 virus, the concept of transfer learning can make a major impact in finding a proper solution in a faster time which is crucial in this case. Transfer learning can be applied in many ways including using it with fine tuning. Each way needs its proper preparations and considerations. The goal of this paper is to explore the subject in detail and go through an extensive comparison on the most widely ways and models using these techniques in methods like classification and clustering.