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The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector

dc.contributor.authorDurrant, Aiden
dc.contributor.authorMarkovic, Milan
dc.contributor.authorMatthews, David
dc.contributor.authorMay, David
dc.contributor.authorEnright, Jessica
dc.contributor.authorLeontidis, Georgios
dc.date.accessioned2023-08-26T23:09:12Z
dc.date.available2023-08-26T23:09:12Z
dc.date.issued2022-02-01
dc.identifier210474584
dc.identifierf95c1100-0f91-4c53-9ec7-04ea45d8fe9a
dc.identifier85122021693
dc.identifier85122021693
dc.identifier.citationDurrant , A , Markovic , M , Matthews , D , May , D , Enright , J & Leontidis , G 2022 , ' The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector ' , Computers and Electronics in Agriculture , vol. 193 , 106648 . https://doi.org/10.1016/j.compag.2021.106648en
dc.identifier.issn0168-1699
dc.identifier.otherORCID: /0000-0001-6671-5568/work/106161491
dc.identifier.otherORCID: /0000-0002-8375-4523/work/148047429
dc.identifier.urihttp://aura-test.abdn.ac.uk/handle/2164/19756
dc.descriptionAcknowledgements This work was supported by an award made by the UKRI/EPSRC funded Internet of Food ThingsNetwork+ grant EP/R045127/1.en
dc.format.extent12
dc.format.extent1892005
dc.language.isoeng
dc.relation.ispartofComputers and Electronics in Agricultureen
dc.subjectSDG 2 - Zero Hungeren
dc.subjectSDG 9 - Industry, Innovation, and Infrastructureen
dc.subject2040 Data and Artificial Intelligenceen
dc.subjectAgri-Fooden
dc.subjectFederated Learningen
dc.subjectMachine Learningen
dc.subjectData Sharingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectEngineering and Physical Sciences Research Council (EPSRC)en
dc.subjectEP/R045127/1en
dc.subject.lccQA75en
dc.titleThe Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sectoren
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen.Trusted Things and Communitiesen
dc.contributor.institutionUniversity of Aberdeen.Vice Principalsen
dc.contributor.institutionUniversity of Aberdeen.Machine Learningen
dc.description.statusPeer revieweden
dc.identifier.doihttps://doi.org/10.1016/j.compag.2021.106648
dc.date.embargoedUntil2022-12-20
dc.identifier.vol193en


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