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Deep learning for automated detection of Drosophila suzukii : potential for UAV-based monitoring

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dc.contributor.authorRoosjen, Peter P.J.
dc.contributor.authorKellenberger, Benjamin
dc.contributor.authorKooistra, Lammert
dc.contributor.authorGreen, David R.
dc.contributor.authorFahrentrapp, Johannes
dc.contributor.institutionUniversity of Aberdeen.Geography & Environmenten
dc.date.accessioned2022-08-08T13:48:00Z
dc.date.available2022-08-08T13:48:00Z
dc.date.issued2020-09-01
dc.descriptionThis work is part of the research programme ERA-net C-IPM 2016 with project number ALW.FACCE.7, which is (partly) financed by the Dutch Research Council (NWO). In Switzerland the project was funded by the Swiss Federal Office of Agriculture (grant 627000782). In the UK the project was supported by DEFRA.en
dc.description.statusPeer revieweden
dc.format.extent9
dc.format.extent7708138
dc.identifier218242096
dc.identifier31f75c5e-9d35-446f-9394-8f5be2bb4ce5
dc.identifier85083725946
dc.identifier32246738
dc.identifier.citationRoosjen, P P J, Kellenberger, B, Kooistra, L, Green, D R & Fahrentrapp, J 2020, 'Deep learning for automated detection of Drosophila suzukii : potential for UAV-based monitoring', Pest Management Science, vol. 76, no. 9, pp. 2994-3002. https://doi.org/10.1002/ps.5845en
dc.identifier.doi10.1002/ps.5845
dc.identifier.iss9en
dc.identifier.issn1526-498X
dc.identifier.otherORCID: /0000-0002-0518-9979/work/118591990
dc.identifier.urihttps://hdl.handle.net/2164/19031
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85083725946&partnerID=8YFLogxKen
dc.identifier.vol76en
dc.language.isoeng
dc.relation.ispartofPest Management Scienceen
dc.subjectdeep learningen
dc.subjectDrosophila suzukiien
dc.subjectintegrated pest management (IPM)en
dc.subjectobject detectionen
dc.subjectunmanned aerial vehicle (UAV)en
dc.subjectG Geography (General)en
dc.subjectAgronomy and Crop Scienceen
dc.subjectInsect Scienceen
dc.subject.lccG1en
dc.titleDeep learning for automated detection of Drosophila suzukii : potential for UAV-based monitoringen
dc.typeJournal articleen

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