Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/42902
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ulhaq, Anwaar | en |
dc.contributor.author | Born, Jannis | en |
dc.contributor.author | Khan, Asim | en |
dc.contributor.author | Gomes, Douglas Pinto Sampaio | en |
dc.contributor.author | Chakraborty, Subrata | en |
dc.contributor.author | Paul, Manoranjan | en |
dc.date.accessioned | 2022-02-21T00:26:13Z | - |
dc.date.available | 2022-02-21T00:26:13Z | - |
dc.date.issued | 2020-10-12 | - |
dc.identifier.citation | IEEE Access, v.8, p. 179437-179456 | en |
dc.identifier.issn | 2169-3536 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/42902 | - |
dc.description.abstract | <p>The COVID-19 pandemic has triggered an urgent call to contribute to the fight against an immense threat to the human population. Computer Vision, as a subfield of artificial intelligence, has enjoyed recent success in solving various complex problems in health care and has the potential to contribute to the fight of controlling COVID-19. In response to this call, computer vision researchers are putting their knowledge base at test to devise effective ways to counter COVID-19 challenge and serve the global community. New contributions are being shared with every passing day. It motivated us to review the recent work, collect information about available research resources, and an indication of future research directions. We want to make it possible for computer vision researchers to find existing and future research directions. This survey article presents a preliminary review of the literature on research community efforts against COVID-19 pandemic.</p> | en |
dc.language | en | en |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en |
dc.relation.ispartof | IEEE Access | en |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.title | COVID-19 Control by Computer Vision Approaches: A Survey | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1109/ACCESS.2020.3027685 | en |
dc.identifier.pmid | 34812357 | en |
dcterms.accessRights | Gold | en |
local.contributor.firstname | Anwaar | en |
local.contributor.firstname | Jannis | en |
local.contributor.firstname | Asim | en |
local.contributor.firstname | Douglas Pinto Sampaio | en |
local.contributor.firstname | Subrata | en |
local.contributor.firstname | Manoranjan | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | schakra3@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | United States of America | en |
local.format.startpage | 179437 | en |
local.format.endpage | 179456 | en |
local.identifier.scopusid | 85099078228 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 8 | en |
local.title.subtitle | A Survey | en |
local.access.fulltext | Yes | en |
local.contributor.lastname | Ulhaq | en |
local.contributor.lastname | Born | en |
local.contributor.lastname | Khan | en |
local.contributor.lastname | Gomes | en |
local.contributor.lastname | Chakraborty | en |
local.contributor.lastname | Paul | en |
dc.identifier.staff | une-id:schakra3 | en |
local.profile.orcid | 0000-0002-0102-5424 | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/42902 | en |
local.date.onlineversion | 2020-09-29 | - |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | COVID-19 Control by Computer Vision Approaches | en |
local.relation.fundingsourcenote | This work was supported by Charles Sturt University, COVID-19 Fund. | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Ulhaq, Anwaar | en |
local.search.author | Born, Jannis | en |
local.search.author | Khan, Asim | en |
local.search.author | Gomes, Douglas Pinto Sampaio | en |
local.search.author | Chakraborty, Subrata | en |
local.search.author | Paul, Manoranjan | en |
local.open.fileurl | https://rune.une.edu.au/web/retrieve/23cdb11c-ba06-4fa3-bb0f-521a83961949 | en |
local.uneassociation | No | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.available | 2020 | en |
local.year.published | 2020 | en |
local.fileurl.open | https://rune.une.edu.au/web/retrieve/23cdb11c-ba06-4fa3-bb0f-521a83961949 | en |
local.fileurl.openpublished | https://rune.une.edu.au/web/retrieve/23cdb11c-ba06-4fa3-bb0f-521a83961949 | en |
local.subject.for2020 | 460102 Applications in health | en |
local.subject.for2020 | 461103 Deep learning | en |
local.subject.for2020 | 460308 Pattern recognition | en |
local.subject.seo2020 | 209999 Other health not elsewhere classified | en |
local.subject.seo2020 | 280115 Expanding knowledge in the information and computing sciences | en |
Appears in Collections: | Journal Article School of Science and Technology |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
openpublished/COVID19Chakraborty2020JournalArticle.pdf | Published Version | 3.32 MB | Adobe PDF Download Adobe | View/Open |
SCOPUSTM
Citations
79
checked on Jul 20, 2024
Page view(s)
1,114
checked on Jan 14, 2024
Download(s)
2
checked on Jan 14, 2024
This item is licensed under a Creative Commons License