  The new Coronavirus is spreading rapidly and it has taken the lives of many
people so far. The virus has destructive effects on the human lung and early
detection is very important. Deep Convolution neural networks are a powerful
tool in classifying images. Therefore, in this paper a hybrid approach based on
a deep network is presented. Feature vectors were extracted by applying a deep
convolution neural network on the images and effective features were selected
by the binary differential meta-heuristic algorithm. These optimized features
were given to the SVM classifier. A database consisting of three categories of
images as COVID-19, pneumonia, and healthy included 1092 X-ray samples was
considered. The proposed method achieved an accuracy of 99.43%, a sensitivity
of 99.16%, and a specificity of 99.57%. Our results demonstrate the suggested
approach is better than recent studies on COVID-19 detection with X-ray images.
