Roosjen, Peter P.J.Kellenberger, BenjaminKooistra, LammertGreen, David R.Fahrentrapp, Johannes2022-08-082022-08-082020-09-01Roosjen, 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.58451526-498XORCID: /0000-0002-0518-9979/work/118591990https://hdl.handle.net/2164/19031This 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.97708138engdeep learningDrosophila suzukiiintegrated pest management (IPM)object detectionunmanned aerial vehicle (UAV)G Geography (General)Agronomy and Crop ScienceInsect ScienceG1Journal article10.1002/ps.5845http://www.scopus.com/inward/record.url?scp=85083725946&partnerID=8YFLogxK769