Abstract
Given the severe global impact of COVID-19, artificial intelligence (AI) is emerging as a critical tool in mitigating the disease's effects by enabling early detection and monitoring of infected individuals. This research proposes a robust system for detecting COVID-19-related lung abnormalities using chest CT images, applying advanced deep learning techniques. The study aims to develop a fully automated and high-speed detection method for COVID-19 from CT scans. The approach utilizes several deep learning architectures, including ResNet50, DenseNet, VGG-16, and U-Net, to accurately classify CT images as either COVID-19 positive or normal. The proposed system achieves a notable classification accuracy of 98.49%, showing its potential for improving diagnostic efficiency and supporting timely treatment decisions