Skip to content

A deep neural network model that classifies an X-ray image into one of the following classes: normal, COVID-19, Pneumonia-Bacterial, and Pneumonia-Viral

Notifications You must be signed in to change notification settings

rsw0/x-ray-classifcation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 

Repository files navigation

x-ray-classifcation

This project seeks to classify a given X-Ray image into one of the following four categories: normal, COVID-19, Pneumonia-Bacterial, and Pneumonia-Viral.

Transfer learning was used to construct the models. Two base models (VGG16 and ResNet) were compared and tuned. The lowest testing loss (0.48077499866485596) was achieved by ResNet, and the testing accuracy for ResNet was 0.7777777910232544. The T-SNE plot for ResNet shows a clear separation among the classes.

The folder "all" contains training and testing data. All codes are included in the Jupyter notebook file. Class project for CS440 at Boston University

About

A deep neural network model that classifies an X-ray image into one of the following classes: normal, COVID-19, Pneumonia-Bacterial, and Pneumonia-Viral

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published