Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/60399
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dc.contributor.authorZhang, Wenjuen
dc.contributor.authorWang, Yaowuen
dc.contributor.authorGuo, Leifengen
dc.contributor.authorFalzon, Gregen
dc.contributor.authorKwan, Paulen
dc.contributor.authorJin, Zhongmingen
dc.contributor.authorLi, Yongfengen
dc.contributor.authorWang, Wenshengen
dc.date.accessioned2024-06-01T11:01:13Z-
dc.date.available2024-06-01T11:01:13Z-
dc.date.issued2024-
dc.identifier.citationAnimals, 14(9), p. 1-15en
dc.identifier.issn2076-2615en
dc.identifier.urihttps://hdl.handle.net/1959.11/60399-
dc.description.abstract<p>Standing and lying are the fundamental behaviours of quadrupedal animals, and the ratio of their durations is a significant indicator of calf health. In this study, we proposed a computer vision method for non-invasively monitoring of calves' behaviours. Cameras were deployed at four viewpoints to monitor six calves on six consecutive days. YOLOv8n was trained to detect standing and lying calves. Daily behavioural budget was then summarised and analysed based on automatic inference on untrained data. The results show a mean average precision of 0.995 and an average inference speed of 333 frames per second. The maximum error in the estimated daily standing and lying time for a total of 8 calf-days is less than 14 min. Calves with diarrhoea had about 2 h more daily lying time (<i>p < 0.002</i>), 2.65 more daily lying bouts (<i>p < 0.049</i>), and 4.3 min less daily lying bout duration (<i>p = 0.5</i>) compared to healthy calves. The proposed method can help in understanding calves' health status based on automatically measured standing and lying time, thereby improving their welfare and management on the farm.</p>en
dc.languageenen
dc.publisherMDPI AGen
dc.relation.ispartofAnimalsen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleAnalysis and Comparison of New-Born Calf Standing and Lying Time Based on Deep Learningen
dc.typeJournal Articleen
dc.identifier.doi10.3390/ani14091324en
dcterms.accessRightsUNE Greenen
local.contributor.firstnameWenjuen
local.contributor.firstnameYaowuen
local.contributor.firstnameLeifengen
local.contributor.firstnameGregen
local.contributor.firstnamePaulen
local.contributor.firstnameZhongmingen
local.contributor.firstnameYongfengen
local.contributor.firstnameWenshengen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailgfalzon2@une.edu.auen
local.profile.emailwkwan2@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeSwitzerlanden
local.identifier.runningnumber1324en
local.format.startpage1en
local.format.endpage15en
local.peerreviewedYesen
local.identifier.volume14en
local.identifier.issue9en
local.access.fulltextYesen
local.contributor.lastnameZhangen
local.contributor.lastnameWangen
local.contributor.lastnameGuoen
local.contributor.lastnameFalzonen
local.contributor.lastnameKwanen
local.contributor.lastnameJinen
local.contributor.lastnameLien
local.contributor.lastnameWangen
dc.identifier.staffune-id:gfalzon2en
dc.identifier.staffune-id:wkwan2en
local.profile.orcid0000-0002-1989-9357en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
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local.identifier.unepublicationidune:1959.11/60399en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleAnalysis and Comparison of New-Born Calf Standing and Lying Time Based on Deep Learningen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorZhang, Wenjuen
local.search.authorWang, Yaowuen
local.search.authorGuo, Leifengen
local.search.authorFalzon, Gregen
local.search.authorKwan, Paulen
local.search.authorJin, Zhongmingen
local.search.authorLi, Yongfengen
local.search.authorWang, Wenshengen
local.open.fileurlhttps://rune.une.edu.au/web/retrieve/7ed3effc-a4c3-4e3e-a5f3-d7d076a95d4den
local.uneassociationYesen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2024en
local.fileurl.openhttps://rune.une.edu.au/web/retrieve/7ed3effc-a4c3-4e3e-a5f3-d7d076a95d4den
local.fileurl.openpublishedhttps://rune.une.edu.au/web/retrieve/7ed3effc-a4c3-4e3e-a5f3-d7d076a95d4den
local.subject.for20203002 Agriculture, land and farm managementen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-06-03en
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School of Science and Technology
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