Term of Award

Summer 2021

Degree Name

Master of Science in Mathematics (M.S.)

Document Type and Release Option

Thesis (restricted to Georgia Southern)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


Department of Mathematical Sciences

Committee Chair

Jiehua Zhu

Committee Member 1

Yan Wu

Committee Member 2

Yongki Lee


In this thesis, we analyze and perform image classification on lung X-Ray images with three state of the art convolutional neural networks. The design of Inception Resnetv2, Weakly Supervised Data Augmentation, and Discriminative Filter Bank convolutional neural networks are analyzed. We conduct image classification using the aforementioned methods with clinical x-ray chest images and review the results. The image set consists of three types of lung conditions: Normal, COVID 19, and Viral Pneumonia. It is shown that these methods effectively detect differences between COVID 19 and Viral Pneumonia.

OCLC Number


Research Data and Supplementary Material