Classification of COVID-19 using Deep Convolutional Neural Network

The COVID-19 pandemic appears to have a devastating impact on the fitness and health of the world's population.Effective screening of infected patients is a critical step in the battle against COVID-19, with chest radiography being one of the main screening methods.In this paper, an Alexnet model based on a deep convolutional neural network with SVM is proposed to automatically detect COVID-19 disease using chest X-ray radiography, while optimizing detection accuracy using deep convolutional neural networks.Furthermore, largescale experiments were performed with an Alexnet pre-trained deep learning model that was used to extract image patterns, and a Support Vector Machine (SVM) was used for the classification process.A support vector machine turned into used to update the higher layers of pre-trained models, trained the usage of off-the-shelf features from the bottom layers.The experimental results showed the validity and efficiency of our proposed model, where obtained an accuracy of 99.7% in classifying