eprintid: 17700
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/77/00
datestamp: 2023-12-19 03:24:02
lastmod: 2023-12-19 03:24:02
status_changed: 2023-12-19 03:08:31
type: article
metadata_visibility: show
creators_name: Jain, S.
creators_name: Sindhwani, N.
creators_name: Anand, R.
creators_name: Kannan, R.
title: COVID Detection Using Chest X-Ray and Transfer Learning
ispublished: pub
note: cited By 29; Conference of 21st International Conference on Intelligent Systems Design and Applications, ISDA 2021 ; Conference Date: 13 December 2021 Through 15 December 2021; Conference Code:275899
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.
date: 2022
publisher: Springer Science and Business Media Deutschland GmbH
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127672464&doi=10.1007%2f978-3-030-96308-8_87&partnerID=40&md5=00f52e3cc1bf92f1756740b882e2905e
id_number: 10.1007/978-3-030-96308-8₈₇
full_text_status: none
publication: Lecture Notes in Networks and Systems
volume: 418 LN
pagerange: 933-943
refereed: TRUE
isbn: 9783030963071
issn: 23673370
citation:   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.  ISSN 23673370