Covid-19 Pneumonia Level Detection Using Deep Learning Algorithm and Transfer Learning

This paper frames the improvement of a deep learning model intended for the exact discovery and order of pneumonia levels (Mild and Severe) in Coronavirus affirmed patients in light of chest X-beam pictures. The model’s development includes the execution of two particular strategies. The primary strategy utilizes a convolutional neural network worked without any preparation to characterize pneumonia levels in Coronavirus affirmed patients. Conversely, the subsequent strategy uses transfer learning with pre-trainedd models for a similar order task. The essential goal of this study is to achieve raised degrees of precision, awareness, and particularity in separating pneumonia levels among Coronavirus affirmed patients by utilizing these two assorted techniques.