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https://hdl.handle.net/1959.11/60399
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zhang, Wenju | en |
dc.contributor.author | Wang, Yaowu | en |
dc.contributor.author | Guo, Leifeng | en |
dc.contributor.author | Falzon, Greg | en |
dc.contributor.author | Kwan, Paul | en |
dc.contributor.author | Jin, Zhongming | en |
dc.contributor.author | Li, Yongfeng | en |
dc.contributor.author | Wang, Wensheng | en |
dc.date.accessioned | 2024-06-01T11:01:13Z | - |
dc.date.available | 2024-06-01T11:01:13Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | Animals, 14(9), p. 1-15 | en |
dc.identifier.issn | 2076-2615 | en |
dc.identifier.uri | https://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.language | en | en |
dc.publisher | MDPI AG | en |
dc.relation.ispartof | Animals | en |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.title | Analysis and Comparison of New-Born Calf Standing and Lying Time Based on Deep Learning | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.3390/ani14091324 | en |
dcterms.accessRights | UNE Green | en |
local.contributor.firstname | Wenju | en |
local.contributor.firstname | Yaowu | en |
local.contributor.firstname | Leifeng | en |
local.contributor.firstname | Greg | en |
local.contributor.firstname | Paul | en |
local.contributor.firstname | Zhongming | en |
local.contributor.firstname | Yongfeng | en |
local.contributor.firstname | Wensheng | en |
local.profile.school | School of Science and Technology | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | gfalzon2@une.edu.au | en |
local.profile.email | wkwan2@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 | Switzerland | en |
local.identifier.runningnumber | 1324 | en |
local.format.startpage | 1 | en |
local.format.endpage | 15 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 14 | en |
local.identifier.issue | 9 | en |
local.access.fulltext | Yes | en |
local.contributor.lastname | Zhang | en |
local.contributor.lastname | Wang | en |
local.contributor.lastname | Guo | en |
local.contributor.lastname | Falzon | en |
local.contributor.lastname | Kwan | en |
local.contributor.lastname | Jin | en |
local.contributor.lastname | Li | en |
local.contributor.lastname | Wang | en |
dc.identifier.staff | une-id:gfalzon2 | en |
dc.identifier.staff | une-id:wkwan2 | en |
local.profile.orcid | 0000-0002-1989-9357 | 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.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/60399 | 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 |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Analysis and Comparison of New-Born Calf Standing and Lying Time Based on Deep Learning | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Zhang, Wenju | en |
local.search.author | Wang, Yaowu | en |
local.search.author | Guo, Leifeng | en |
local.search.author | Falzon, Greg | en |
local.search.author | Kwan, Paul | en |
local.search.author | Jin, Zhongming | en |
local.search.author | Li, Yongfeng | en |
local.search.author | Wang, Wensheng | en |
local.open.fileurl | https://rune.une.edu.au/web/retrieve/7ed3effc-a4c3-4e3e-a5f3-d7d076a95d4d | en |
local.uneassociation | Yes | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.published | 2024 | en |
local.fileurl.open | https://rune.une.edu.au/web/retrieve/7ed3effc-a4c3-4e3e-a5f3-d7d076a95d4d | en |
local.fileurl.openpublished | https://rune.une.edu.au/web/retrieve/7ed3effc-a4c3-4e3e-a5f3-d7d076a95d4d | en |
local.subject.for2020 | 3002 Agriculture, land and farm management | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | UNE Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.date.moved | 2024-06-03 | en |
Appears in Collections: | Journal Article School of Science and Technology |
Files in This Item:
File | Description | Size | Format | |
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openpublished/AnalysisFalzonKwan2024JournalArticle.pdf | Published version | 4.83 MB | Adobe PDF Download Adobe | View/Open |
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