A Comparison of Deep Learning Models for Detecting COVID-19 in Chest X-ray Images.

COVID-19 has spread around the world rapidly causing a pandemic. In this research, a set of Deep Learning architectures, for diagnosing the presence or not of the disease have been designed and compared; such as, a CNN with 4 incremental convolutional blocks; a VGG-19 architecture; an Inception network; and, a compact CNN model known as MobileNet. For the analysis and comparison, transfer learning techniques were used in forty-five different experiments.