Spectral analysis and mapping of blackgrass weed by leveraging machine learning and UAV multispectral imagery

Su, JinyaYi, DeweiCoombes, MatthewLiu, CunjiaZhai, XiaojunMcDonald-Maier, KlausChen, Wen Hua2022-12-052022-12-052022-01-01Su, J, Yi, D, Coombes, M, Liu, C, Zhai, X, McDonald-Maier, K & Chen, W H 2022, 'Spectral analysis and mapping of blackgrass weed by leveraging machine learning and UAV multispectral imagery', Computers and Electronics in Agriculture, vol. 192, 106621. https://doi.org/10.1016/j.compag.2021.1066210168-1699ORCID: /0000-0003-1702-9136/work/106597852ORCID: /0000-0002-3121-7208/work/112496143https://hdl.handle.net/2164/19678Acknowledgements This work was supported by Science and Technology Facilities Council (STFC) with grant numbers ST/N006852/1 and ST/V00137X/1.113471628engSubstantive connection via an eligible employment contractBlackgrass weedGuided filterRandom forestSpectral Index (SI)unmanned aerial vehicle (UAV)QA75 Electronic computers. Computer scienceForestryAgronomy and Crop ScienceComputer Science ApplicationsHorticultureSTFC - Science and Technology Facilities CouncilST/N006852/1ST/V00137X/1QA75Spectral analysis and mapping of blackgrass weed by leveraging machine learning and UAV multispectral imageryJournal article10.1016/j.compag.2021.106621http://www.scopus.com/inward/record.url?scp=85121118573&partnerID=8YFLogxK