Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/14259
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dc.contributor.authorArıkan, İ.-
dc.contributor.authorAyav, T.-
dc.contributor.authorSeçkin, A.Ç.-
dc.contributor.authorSoygazi, F.-
dc.date.accessioned2024-01-30T09:24:44Z-
dc.date.available2024-01-30T09:24:44Z-
dc.date.issued2023-
dc.identifier.issn1424-8220-
dc.identifier.urihttps://doi.org/10.3390/s23249795-
dc.identifier.urihttps://hdl.handle.net/11147/14259-
dc.description.abstractAccurate 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.language.isoenen_US
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en_US
dc.relation.ispartofSensorsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectartificial intelligenceen_US
dc.subjectaugmented realityen_US
dc.subjectdairy cow identificationen_US
dc.subjectdeep learningen_US
dc.subjectestrus detectionen_US
dc.subjectimage processingen_US
dc.subjectlivestocken_US
dc.subjectprecision livestock farmingen_US
dc.subjecttransfer learningen_US
dc.subjectAugmented realityen_US
dc.subjectDairiesen_US
dc.subjectDeep learningen_US
dc.subjectFarmsen_US
dc.subjectImage segmentationen_US
dc.subjectLossesen_US
dc.subjectDairy cowen_US
dc.subjectDairy cow identificationen_US
dc.subjectDeep learningen_US
dc.subjectEstrus detectionen_US
dc.subjectImages processingen_US
dc.subjectLivestocken_US
dc.subjectPrecision livestock farmingen_US
dc.subjectRegion-of-interesten_US
dc.subjectRegions of interesten_US
dc.subjectTransfer learningen_US
dc.subjectMountingsen_US
dc.subjectanimalen_US
dc.subjectartificial intelligenceen_US
dc.subjectaugmented realityen_US
dc.subjectbovineen_US
dc.subjectdairyingen_US
dc.subjectdeep learningen_US
dc.subjectestrusen_US
dc.subjectfemaleen_US
dc.subjectlivestocken_US
dc.subjectmilken_US
dc.subjectproceduresen_US
dc.subjectAnimalsen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectAugmented Realityen_US
dc.subjectCattleen_US
dc.subjectDairyingen_US
dc.subjectDeep Learningen_US
dc.subjectEstrus Detectionen_US
dc.subjectFemaleen_US
dc.subjectLivestocken_US
dc.subjectMilken_US
dc.titleEstrus Detection and Dairy Cow Identification with Cascade Deep Learning for Augmented Reality-Ready Livestock Farmingen_US
dc.typeArticleen_US
dc.institutionauthor-
dc.departmentİzmir Institute of Technologyen_US
dc.identifier.volume23en_US
dc.identifier.issue24en_US
dc.identifier.scopus2-s2.0-85180616159en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.3390/s23249795-
dc.identifier.pmid38139641en_US
dc.authorscopusid58781072000-
dc.authorscopusid13408184500-
dc.authorscopusid57103461800-
dc.authorscopusid57220960947-
dc.identifier.wosqualityQ2-
dc.identifier.scopusqualityQ2-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeArticle-
crisitem.author.dept03.04. Department of Computer Engineering-
Appears in Collections:PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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