Research on classification of COVID-19 and common pneumonia by x-ray images based on convolutional attention mechanism

As the COVID-19 pandemic spreads across the globe, it highlights the importance of using all available resources to mitigate this common human challenge. Therefore, this paper studies and evaluates the general convolutional neural network and a method based on lung X-ray image classification. Attention mechanism mechanism + DenesNet method for detecting infected patients from chest X-ray images. In order to improve the validity, the mixed data set is preprocessed in this paper. In order to reduce the problem of small number of samples, we adopt transfer learning to transfer the information extracted from the pre-trained model to the model to be trained. The experimental results show that the overall accuracy of the design experiment in this paper has been improved to a certain extent compared with the original network model, and the overall accuracy has reached 83.82%.