Detection of Covid-19 from X-Ray Images Using Deep Learning

Authors

  • S. Karthikeyan Student, Department of Electronics and Communication Engineering, Velammal College of Engineering and Technology, Madurai, India
  • A. R. Aravind Student, Department of Electronics and Communication Engineering, Velammal College of Engineering and Technology, Madurai, India
  • S. Ajay Surya Student, Department of Electronics and Communication Engineering, Velammal College of Engineering and Technology, Madurai, India
  • A. Alaimahal Student, Department of Electronics and Communication Engineering, Velammal College of Engineering and Technology, Madurai, India

Keywords:

Covid-19, Deep Learning, Darknet-19, YOLO

Abstract

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus. It is critical to detect the positive cases as early as possible so as to prevent the further spread of this epidemic and to quickly treat affected patients. To overcome this difficulty, we have developed a model using deep learning to detect covid-19 from x-ray images. This project aims to develop a model using Darknet-19 as a classifier for the you only look once (YOLO) real time object detection system. This project provides accurate diagnostics for binary classification (COVID vs. No-Findings).

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Published

29-07-2021

Issue

Vol. 2 No. 7 (2021)

Section

Articles

License

Copyright (c) 2021 S. Karthikeyan, A. R. Aravind, S. Ajay Surya, A. Alaimahal

Creative Commons License

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

How to Cite

[1]
S. Karthikeyan, A. R. Aravind, S. Ajay Surya, and A. Alaimahal, “Detection of Covid-19 from X-Ray Images Using Deep Learning”, IJRAMT, vol. 2, no. 7, pp. 246–248, Jul. 2021, Accessed: Dec. 22, 2024. [Online]. Available: https://journals.ijramt.com/index.php/ijramt/article/view/1097