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Coronavirus adversely has affected people worldwide. There are commonsymptoms between the Covid19 virus disease and other respiratory diseases likepneumonia or Influenza. Therefore, diagnosing it fast is crucial not only tosave patients but also to prevent it from spreading. One of the most reliantmethods of diagnosis is through X-ray images of a lung. With the help of deeplearning approaches, we can teach the deep model to learn the condition of anaffected lung. Therefore, it can classify the new sample as if it is a Covid19infected patient or not. In this project, we train a deep model based onResNet50 pretrained by ImageNet dataset and CheXNet dataset. Based on theimbalanced CoronaHack Chest X-Ray dataset introducing by Kaggle we applied bothbinary and multi-class classification. Also, we compare the results when usingFocal loss and Cross entropy loss.

Transfer learning approach to Classify the X-ray image that corresponds to corona disease Using ResNet50 pretrained by ChexNet