Detecting COVID using CNN from Chest X-Beams

ABSTRACT

Since inception of Corona Virus, 47.6 Cr. individuals got infected and 61L deaths occurred. Still it's going on and spreading across the world. Many health workers, researchers, experts, scientists are making efforts to slow down its pace & putting efforts in evaluating the techniques to detect it. For this, it is highly required to understand the virus & its versions. It is a part of SARS - Severe acute respiratory syndrome. To detect COVID, there are numerous ways but using Chest X-beams we are able to reduce the detection time and cost. To evaluate the Chest X-beams we need radiologists. So here, we develop a model to identify COVID X-beam in comparison to Normal X-beam. These days DL algo's are producing best results in classification. A pre-trained CNN models using large datasets is to preferred for image classification. Firstly our models need to be trained and then tested to recognize the images of X-beams of one of the either case. Logically we have to locate the best CNN model for diagnosis. © 2022 IEEE.