Diagnosis of COVID-19 and Pneumonia using Depthwise Separable Convolutional Neural Network

COVID-19 disease is a consequence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that came to light as an epidemic over the planet. The long-established diagnostic systems are confronting difficulties in identifying the virus expeditiously in the initial stages. In these circumstances, chest X-ray scans can be beneficial for the identification of COVID-19 as well as pneumonia. On that account, in this research, a deep convolution neural network having depthwise separable convolutions has been put forward to look over the chest X-ray scans for identifying COVID-19 and pneumonia precisely. The propounded model with only 0.18 million parameters has been employed on various standard datasets and performs significantly faster than other state-of-the-art models and the exploratory results explain the potency of the propounded approach.