COVID Detection Using Chest X-Ray and Transfer Learning
21st International Conference on Intelligent Systems Design and Applications, ISDA 2021
; 418 LNNS:933-943, 2022.
Article
in English
| Scopus | ID: covidwho-1787720
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.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
21st International Conference on Intelligent Systems Design and Applications, ISDA 2021
Year:
2022
Document Type:
Article
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