Estrus Detection and Dairy Cow Identification With Cascade Deep Learning for Augmented Reality-Ready Livestock Farming

dc.contributor.author Arıkan, İ.
dc.contributor.author Ayav, T.
dc.contributor.author Seçkin, A.Ç.
dc.contributor.author Soygazi, F.
dc.date.accessioned 2024-01-30T09:24:44Z
dc.date.available 2024-01-30T09:24:44Z
dc.date.issued 2023
dc.description.abstract Accurate prediction of the estrus period is crucial for optimizing insemination efficiency and reducing costs in animal husbandry, a vital sector for global food production. Precise estrus period determination is essential to avoid economic losses, such as milk production reductions, delayed calf births, and disqualification from government support. The proposed method integrates estrus period detection with cow identification using augmented reality (AR). It initiates deep learning-based mounting detection, followed by identifying the mounting region of interest (ROI) using YOLOv5. The ROI is then cropped with padding, and cow ID detection is executed using YOLOv5 on the cropped ROI. The system subsequently records the identified cow IDs. The proposed system accurately detects mounting behavior with 99% accuracy, identifies the ROI where mounting occurs with 98% accuracy, and detects the mounting couple with 94% accuracy. The high success of all operations with the proposed system demonstrates its potential contribution to AR and artificial intelligence applications in livestock farming. © 2023 by the authors. en_US
dc.identifier.doi 10.3390/s23249795
dc.identifier.issn 1424-8220
dc.identifier.scopus 2-s2.0-85180616159
dc.identifier.uri https://doi.org/10.3390/s23249795
dc.identifier.uri https://hdl.handle.net/11147/14259
dc.language.iso en en_US
dc.publisher Multidisciplinary Digital Publishing Institute (MDPI) en_US
dc.relation.ispartof Sensors en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject artificial intelligence en_US
dc.subject augmented reality en_US
dc.subject dairy cow identification en_US
dc.subject deep learning en_US
dc.subject estrus detection en_US
dc.subject image processing en_US
dc.subject livestock en_US
dc.subject precision livestock farming en_US
dc.subject transfer learning en_US
dc.subject Augmented reality en_US
dc.subject Dairies en_US
dc.subject Deep learning en_US
dc.subject Farms en_US
dc.subject Image segmentation en_US
dc.subject Losses en_US
dc.subject Dairy cow en_US
dc.subject Dairy cow identification en_US
dc.subject Deep learning en_US
dc.subject Estrus detection en_US
dc.subject Images processing en_US
dc.subject Livestock en_US
dc.subject Precision livestock farming en_US
dc.subject Region-of-interest en_US
dc.subject Regions of interest en_US
dc.subject Transfer learning en_US
dc.subject Mountings en_US
dc.subject animal en_US
dc.subject artificial intelligence en_US
dc.subject augmented reality en_US
dc.subject bovine en_US
dc.subject dairying en_US
dc.subject deep learning en_US
dc.subject estrus en_US
dc.subject female en_US
dc.subject livestock en_US
dc.subject milk en_US
dc.subject procedures en_US
dc.subject Animals en_US
dc.subject Artificial Intelligence en_US
dc.subject Augmented Reality en_US
dc.subject Cattle en_US
dc.subject Dairying en_US
dc.subject Deep Learning en_US
dc.subject Estrus Detection en_US
dc.subject Female en_US
dc.subject Livestock en_US
dc.subject Milk en_US
dc.title Estrus Detection and Dairy Cow Identification With Cascade Deep Learning for Augmented Reality-Ready Livestock Farming en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional
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gdc.author.scopusid 57103461800
gdc.author.scopusid 57220960947
gdc.bip.impulseclass C4
gdc.bip.influenceclass C5
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Institute of Technology en_US
gdc.description.departmenttemp Arıkan, İ., Computer Engineering Department, İzmir Institute of Technology, Izmir, 35430, Turkey; Ayav, T., Computer Engineering Department, İzmir Institute of Technology, Izmir, 35430, Turkey; Seçkin, A.Ç., Computer Engineering Department, Aydın Adnan Menderes University, Aydın, 09100, Turkey; Soygazi, F., Computer Engineering Department, Aydın Adnan Menderes University, Aydın, 09100, Turkey en_US
gdc.description.issue 24 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.volume 23 en_US
gdc.description.wosquality Q2
gdc.identifier.openalex W4389670395
gdc.identifier.pmid 38139641
gdc.index.type Scopus
gdc.index.type PubMed
gdc.oaire.accesstype GOLD
gdc.oaire.diamondjournal false
gdc.oaire.impulse 14.0
gdc.oaire.influence 3.3725922E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Livestock
gdc.oaire.keywords Augmented Reality
gdc.oaire.keywords Chemical technology
gdc.oaire.keywords deep learning
gdc.oaire.keywords TP1-1185
gdc.oaire.keywords artificial intelligence
gdc.oaire.keywords augmented reality
gdc.oaire.keywords Article
gdc.oaire.keywords dairy cow identification
gdc.oaire.keywords image processing
gdc.oaire.keywords Dairying
gdc.oaire.keywords Deep Learning
gdc.oaire.keywords Milk
gdc.oaire.keywords Artificial Intelligence
gdc.oaire.keywords estrus detection
gdc.oaire.keywords Animals
gdc.oaire.keywords Female
gdc.oaire.keywords Cattle
gdc.oaire.keywords Estrus Detection
gdc.oaire.popularity 7.2785693E-9
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gdc.oaire.sciencefields 04 agricultural and veterinary sciences
gdc.oaire.sciencefields 02 engineering and technology
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 0401 agriculture, forestry, and fisheries
gdc.openalex.collaboration National
gdc.openalex.fwci 5.58535128
gdc.openalex.normalizedpercentile 0.94
gdc.openalex.toppercent TOP 10%
gdc.opencitations.count 0
gdc.plumx.mendeley 61
gdc.plumx.newscount 1
gdc.plumx.pubmedcites 3
gdc.plumx.scopuscites 20
gdc.scopus.citedcount 20
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relation.isOrgUnitOfPublication.latestForDiscovery 9af2b05f-28ac-4014-8abe-a4dfe192da5e

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