An ensemble learning based approach to autonomous COVID19 detection using transfer learning with the help of pre-trained Deep Neural Network models

Abstract

An automated means for predicting the virus is of utmost importance to help the medical personnel to detect patients, prepare reports and produce results fast and impeccably so that people can get early treatment and prevent future transmissions. In this work, we proposed a COVID19 detection method using chest x-ray images by training and testing pre-trained deep neural network models, such as VGG19, InceptionV3, and Densenet201 individually, and got an accuracy of 96.9%, 95.2%, and 96.7% respectively. Then to bolster the performance of each model, we proposed an average weighted based ensemble approach and got an accuracy of 97.5%, which surpassed the performance of each separate model.