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dc.contributor.authorKamilaris, Andreas
dc.contributor.authorPrenafeta-Boldú, Francesc X.
dc.contributor.otherProducció Animalca
dc.date.accessioned2019-04-16T13:26:02Z
dc.date.available2020-02-22T23:01:20Z
dc.date.issued2018-02-22
dc.identifier.citationKamilaris, Andreas, and Francesc X. Prenafeta-Boldú. 2018. "Deep Learning In Agriculture: A Survey". Computers And Electronics In Agriculture 147: 70-90. Elsevier BV. doi:10.1016/j.compag.2018.02.016.ca
dc.identifier.issn0168-1699ca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/314
dc.description.abstractDeep learning constitutes a recent, modern technique for image processing and data analysis, with promising results and large potential. As deep learning has been successfully applied in various domains, it has recently entered also the domain of agriculture. In this paper, we perform a survey of 40 research efforts that employ deep learning techniques, applied to various agricultural and food production challenges. We examine the particular agricultural problems under study, the specific models and frameworks employed, the sources, nature and pre-processing of data used, and the overall performance achieved according to the metrics used at each work under study. Moreover, we study comparisons of deep learning with other existing popular techniques, in respect to differences in classification or regression performance. Our findings indicate that deep learning provides high accuracy, outperforming existing commonly used image processing techniques.ca
dc.format.extent54ca
dc.language.isoengca
dc.publisherElsevierca
dc.relation.ispartofComputers and Electronics in Agricultureca
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleDeep learning in agriculture: A surveyca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/acceptedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.relation.projectIDEC/H2020/665919/EU/Opening Sphere UAB-CEI to PostDoctoral Fellows/P-SPHEREca
dc.subject.udc63ca
dc.identifier.doihttps://doi.org/10.1016/j.compag.2018.02.016ca
dc.contributor.groupSostenibilitat en Biosistemesca


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Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/