Jain, S. and Sindhwani, N. and Anand, R. and Kannan, R. (2022) COVID Detection Using Chest X-Ray and Transfer Learning. Lecture Notes in Networks and Systems, 418 LN. pp. 933-943.
Full text not available from this repository.Abstract
As per World Health Organization, COVID-19 is causing even the most important health systems across the countries under considerable strain. The advanced recognition of COVID 19 will result into decreasing the stress of a lot of health systems. Much similar to the customary usage of Chest X-Rays for detecting different pathologies, COVID-19 can also be detected using X-Ray of patients that indicates a very critical function in the diagnosis of SARS Covid-19. With rampant growth in the area of Deep Learning (DL) as well as Machine Learning (ML), it is much easier to design the framework that can detect COVID-19 infection easily. This paper proposes deep learning-based detection process by incorporating the concept of Transfer Learning for the classification of this pandemic using X-ray images of chest. This non-invasive and early-prediction of the corona virus by observing the X-rays of chest can subsequently be utilized to estimate the expansion of COVID-19 in the patients. This study got a maximum of 97 classifiers� accuracy using ResNet based model. This method can be utilized to upscale the effectiveness of the screening process. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Item Type: | Article |
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Impact Factor: | cited By 0 |
Depositing User: | Ms Sharifah Fahimah Saiyed Yeop |
Date Deposited: | 26 Jul 2022 06:31 |
Last Modified: | 26 Jul 2022 06:32 |
URI: | http://scholars.utp.edu.my/id/eprint/33271 |