Detection of COVID-19 using Modified VGG Architectures

Abstract

COVID-19 has created havoc in the world. This paper aims to study and understand the performance of modified VGG-16 and VGG-19 architectures in detecting COVID-19 using the concept of transfer learning. The algorithm has been validated using a private dataset with normal and COVID-19 positive chest X-ray images. COVID-19 has created havoc in the world. This paper aims to study and understand the performance of modified VGG-16 and VGG-19 architectures in detecting COVID-19 using the concept of transfer learning. The algorithm has been validated using a private dataset with normal and COVID-19 positive chest X-ray images.