COVID19 Chest X-Ray Classification with Simple Convolutional Neural Network

Abstract

COVID-19 outbreak calls for the urgent need of quick, accurate, and accessible methods for detection. Convolutional neural networks applied to chest x-ray images is a promising solution; however, x-ray device configurations vary and data quality across different datasets are inconsistent. This leads to overfitting on a particular set of training data. This paper aims to explore methods to mitigate overfitting.