COVID-CLNet

One of the most serious global health threats is COVID-19 pandemic. The emphasis on increasing diagnostic capability helps stopping its spread significantly. Therefore, to assist radiologist or other medical professional detect and identify cases in shortest possible time, we propose a computer-aided detection (CADe) system that uses computed tomography (CT) scan images. This proposed boosted deep learning network (CLNet) based implementation Deep Learning (DL) networks as complementary Compressive (CL). We utilize our inception feature extraction technique measurement domain using CL represent data features into new space with less dimensionality before accessing Convolutional Neural Network. All original have been contributed equally sensing matrix. Experiments performed different compressed methods show promising results for detection.