Detection of Covid-19 and Pneumonia in chest X-ray Images using deep learning techniques

The distinction between COVID-19 and pneu-monia from chest X-ray residue is challenging due to their overlay visual features. This study proposes a comparison of the accuracy and efficiency of diagnosis when using augmentation and enhancement methods on chest X-ray images applying them on VGG-16 model, as well as applying them on the VGG-16 model without enhancement. With a dataset of 5970 X-ray images, the model achieved an accuracy of 92.72%, surpassing the performance of tra- ditional methods. These results suggest that deep learning can play a crucial role in enhancing the early detection of COVID-19 and pneumonia.