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dc.contributor.authorWelhenge, Anuradhi
dc.date.accessioned2024-06-26T09:28:08Z
dc.date.available2024-06-26T09:28:08Z
dc.date.issued2021
dc.identifier.citationWelhenge, A. 2021. A Fog Computing-based System to Identify SARS - CoV -2 Using Deep Learning. In 23rd PARIS International Conference on Advances in Science, Engineering and Waste Management, 7 - 9 Dec 2021. Paris, France.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/95411
dc.description.abstract

SARS-CoV-2 has spread all over the world starting from 2019. One of the reasons for this widespread is because detection procedures were not in place. Another reason is that the detection methods like Polymerase Chain Reaction (PCR) test and antigen test are not fast enough and not accurate enough. Another method of detection of the disease is to use medical imaging. Ultrasounds have proven to have good accuracy over X ray scans and therefore, ultrasound images are used in this study to detect Covid 19 patients. For this purpose, a fog computing based deep learning technique is introduced which can be easily implemented in hospitals. This study achieved good accuracy.

dc.titleA Fog Computing-based System to Identify SARS - CoV -2 Using Deep Learning
dc.typeConference Paper
dcterms.source.conference23rd PARIS International Conference on Advances in Science, Engineering and Waste Management
dcterms.source.conference-start-dateDec 7 2021
dcterms.source.conferencelocationParis, France
dc.date.updated2024-06-26T09:28:04Z
curtin.departmentSchool of Elec Eng, Comp and Math Sci (EECMS)
curtin.accessStatusFulltext not available
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidWelhenge, Anuradhi [0000-0001-9219-2246]
dcterms.source.conference-end-dateDec 9 2021
curtin.contributor.scopusauthoridWelhenge, Anuradhi [56604130200]
curtin.repositoryagreementV3


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