Automated Covid-19 Detection With Convolutional Neural Networks

This paper reviews the literature on deep neural networks (DNNs) and machine learning algorithms for the detection and classification of COVID-19 in lung images. It examines the advancements made by previous studies in the field and identifies existing gaps that can be addressed and contribute to. The authors conducted a comparative investigation of various standard CNN models to identify an appropriate model for detecting COVID-19 and optimized it for the imaging modalities to address the challenges posed by the rare and complex nature of the disease.