Show simple item record

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

dc.contributor.authorRoosjen, Peter P.J.
dc.contributor.authorKellenberger, Benjamin
dc.contributor.authorKooistra, Lammert
dc.contributor.authorGreen, David R.
dc.contributor.authorFahrentrapp, Johannes
dc.date.accessioned2022-08-08T13:48:00Z
dc.date.available2022-08-08T13:48:00Z
dc.date.issued2020-09-01
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.issn1526-498X
dc.identifier.otherORCID: /0000-0002-0518-9979/work/118591990
dc.identifier.urihttps://hdl.handle.net/2164/19031
dc.descriptionFunding Information: This 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. Funding Information: This 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. Publisher Copyright: © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.en
dc.format.extent9
dc.format.extent7708138
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
dc.contributor.institutionUniversity of Aberdeen.Geography & Environmenten
dc.description.statusPeer revieweden
dc.identifier.doihttps://doi.org/10.1002/ps.5845
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85083725946&partnerID=8YFLogxKen
dc.identifier.vol76en
dc.identifier.iss9en


Files in this item

Thumbnail
Name:
Roosjen_et_al_Deep_learning_Pe ...
Size:
7.351Mb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record