Detection of COVID-19 in X-ray images by classification of bag of visual words using neural networks

Summary: This study investigated the fine tuning of pretrained convolutional neural networks for COVID-19 classification using chest X-rays. Three pretrained CNNs achieved high classification results without data augmentation, with AlexNet, GoogleNet, and SqueezeNet requiring the least training time among pretrained DL models. These findings contribute to the urgent need for deploying AI tools in the public domain for rapid implementation during the pandemic.