 This research proposes a novel approach for detecting COVID-19 and pneumonia from medical CT and radiography images. It employs deep learning and artificial intelligence techniques to improve the accuracy and precision of the models. The research utilizes transfer learning to address content gaps and shorten training time. Additionally, it applies upgraded VGG-16 and ResNet-152 architectures to classify X-ray images with high accuracy. The results show that the proposed model outperformed other approaches in terms of accuracy and precision. Furthermore, the model was able to accurately differentiate between COVID-19 and pneumonia cases. This article was authored by Shinshi Shua, Silamul Chinna Parimal, Guida Matashara Abdulsahib and others.