Detection of Coronavirus Disease in Human Body Using Convolutional Neural Network

  • Mohit Tiwari, Tripti Tiwari, Manal Kassab, Anit .N. Roy, Deepa Chaudhary, Edeh Michael Onyema

Abstract

Deep learning has developed as another zone in Artificial Intelligence (AI) that can be applied to
various fields of our daily life to solve problems. The Coronavirus Disease 2019 (COVID-19) is
perhaps the world’s biggest problem at the moment. Considering the emerging potentials of Deep
learning- Convolutional Neural Network (CNN), the study developed an optimized deep learning
model of CNN that can detect and classify COVI- 19 infections in human efficiently. The work consists
of an optimized CNN models and experimental analysis of each model towards the detection and
classification of COVID-19. We trained image dataset using the trained CNN model and the result
shows 95 percent accuracy. The findings show that CNN can be used to effectively detect Coronavirus
in human body since the trained model accomplished high accuracy in image classification.

Published
2020-04-13
How to Cite
Mohit Tiwari, Tripti Tiwari, Manal Kassab, Anit .N. Roy, Deepa Chaudhary, Edeh Michael Onyema. (2020). Detection of Coronavirus Disease in Human Body Using Convolutional Neural Network. International Journal of Advanced Science and Technology, 29(8s), 2861-2866. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/16165