基于深度学习的方法检测胸部X射线图像中COVID-19的实证研究

COVID-19病毒的传播增加了提供测试套件的努力。这些试剂盒的制备不仅困难，稀有和昂贵，而且使用它们是另一个问题。..

An Empirical Study on Detecting COVID-19 in Chest X-ray Images Using Deep Learning Based Methods

Spreading of COVID-19 virus has increased the efforts to provide testing kits. Not only the preparation of these kits had been hard, rare, and expensive but also using them is another issue.Results have shown that these kits take some crucial time to recognize the virus, in addition to the fact that they encounter with 30% loss. In this paper, we have studied the usage of x-ray pictures which are ubiquitous, for the classification of COVID-19 chest Xray images, by the existing convolutional neural networks (CNNs). We intend to train chest x-rays of infected and not infected ones with different CNNs architectures including VGG19, Densnet-121, and Xception. Training these architectures resulted in different accuracies which were much faster and more precise than usual ways of testing.