Under the patronage of the Dean of the College of Computer Science and Information Technology, the Department of Computer Science at the College organized a scientific lecture entitled “Diagnosing infection with the Covid 19 virus” delivered by a master’s graduate student (Ali Salman), where he explained in his research study, which consisted of three stages, in the first stage the use of deep learning (Deep Learning) to diagnose COVID-19 by building a convolutional neural network (CNN) from scratch to classify chest x-ray images. Then, the processed data was classified into infected or healthy using Transfer Learning approach model in order to increase network performance in COVID-19 diagnosis to obtain deep features of the used images. In addition to using the Visual Geometry Group (VGG16) model. In his study, the student obtained a training accuracy of 99.992% and an accuracy of 94.33%. The best performing transfer learning model, built from scratch, has a training accuracy of 98.67% and a verification accuracy of 94.67%.
