DEEP-LEARNING-WITH-COVID-19-XRAY-CONVOLUTED-NEURAL-NETWORK

[Disclaimer: Please note that this project is not scientifically tested or prepared for use in any other setting than a personal project.]

I decided to take on the project of identifying whether X-ray imagery of lungs contained COVID-19 virus or were healthy. Through doing this I was able to study various types of convolutional neural networks, image classification, and real world example of model analysis and where shortcomings working with real problems.

Corresponding Medium Blog -->

I treated this project as a learning process, and while making my own decisions about what to implement ultimately, I did find the following articles to be very educational and guide me in the right directions.

-->https://www.pyimagesearch.com/2020/03/16/detecting-covid-19-in-x-ray-images-with-keras-tensorflow-and-deep-learning/

Info on Googlenet Inception CNN -->https://towardsdatascience.com/a-simple-guide-to-the-versions-of-the-inception-network-7fc52b863202

Information on VGG16 CNN -->https://neurohive.io/en/popular-networks/vgg16/