Deep Learning-Based COVID-19 Detection Using Transfer Learning Through ResNet-50

Catering to the widespread COVID-19 pandemic, the authors aim to develop a system based on machine learning combined with the knowledge of medical science. Considering the prevailing situation, it becomes necessary to diagnose the COVID-19 at initial stages. The idea behind the described designed model is to identify the spread of infection in patients as fast as possible. The paper sketches two different approaches: K-fold cross-validation and deep network designer which are based on deep learning technology for the prediction of COVID-19 in the initial stages by using the chest X-rays. The performance evaluation of the cross-fold validation process is compared with the designed application in the deep network designer to find an effective and efficient methodology for classification which attained better accuracy.