A Fog Computing-based System to Identify SARS - CoV -2 Using Deep Learning
dc.contributor.author | Welhenge, Anuradhi | |
dc.date.accessioned | 2024-06-26T09:28:08Z | |
dc.date.available | 2024-06-26T09:28:08Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Welhenge, 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.uri | http://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.title | A Fog Computing-based System to Identify SARS - CoV -2 Using Deep Learning | |
dc.type | Conference Paper | |
dcterms.source.conference | 23rd PARIS International Conference on Advances in Science, Engineering and Waste Management | |
dcterms.source.conference-start-date | Dec 7 2021 | |
dcterms.source.conferencelocation | Paris, France | |
dc.date.updated | 2024-06-26T09:28:04Z | |
curtin.department | School of Elec Eng, Comp and Math Sci (EECMS) | |
curtin.accessStatus | Fulltext not available | |
curtin.faculty | Faculty of Science and Engineering | |
curtin.contributor.orcid | Welhenge, Anuradhi [0000-0001-9219-2246] | |
dcterms.source.conference-end-date | Dec 9 2021 | |
curtin.contributor.scopusauthorid | Welhenge, Anuradhi [56604130200] | |
curtin.repositoryagreement | V3 |