Classification Of X-ray Images For Detecting Covid-19 Using Deep Transfer Learning

The coronavirus disease COVID-19 eruption is stated as a pandemic by the World Health Organization. It is affecting around 212 countries and territories across the globe. There is a need to constantly analyze and find patterns from lungs X-Ray images. Early diagnosis can constraint the exposure of person and aids to bound the feast of the virus. The manual diagnosis is quite tedious and time-consuming process. The main aim of this paper is to explore the transfer learning potential. A deep learning framework is proposed adopting the capability of pretrained Deep Convolutional Neural Network models with transfer learning. This assists in classification of the chest X-Ray Images with high level of accuracy. An analysis is done with utilization of six pretrained models – VGG16, VGG19, ResNet50V2, InceptionV3, Xception and NASNetLarge. The experiment results showed that the highest accuracy obtained was 97% using VGG16 and VGG19 with sensitivity and specificity of 100% and 94% respectively.