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Ai applications in forest monitoring need remote sensing benchmark datasets

dc.contributor.authorLines, E. R.
dc.contributor.authorAllen, M.
dc.contributor.authorCabo Gómez, Carlos 
dc.contributor.authorCalders, K.
dc.contributor.authorDebus, A.
dc.contributor.authorGrieve, S. W. D.
dc.contributor.authorMiltiadou, M.
dc.contributor.authorNoach, A.
dc.contributor.authorOwen, H. J. F.
dc.contributor.authorPuliti, S.
dc.date.accessioned2023-05-18T08:19:28Z
dc.date.available2023-05-18T08:19:28Z
dc.date.issued2022
dc.identifier.isbn9781665480451
dc.identifier.urihttp://hdl.handle.net/10651/67792
dc.descriptionIEEE International Conference on Big Data, Big Data 2022 (2022. Osaka, Japón)
dc.description.sponsorshipE. R. L., S. W. D. G, M. M. and H. J. F. O. were funded by a UKRI Future Leaders Fellowship (MR/T019832/1). E.R.L. was also supported by the Alan Turing Institute. M. A. was supported by the UKRI Centre for Doctoral Training in Application of Artificial Intelligence to the study of Environmental Risks (EP/S022961/1). C. C. was funded by a María Zambrano Grant (Spain; MU-21-UP2021_030) and the Natural Environmental Research Council (UK; NE/T001194/1) K.C was funded by the European Union (ERC-2021-STG Grant agreement No. 101039795) (...)
dc.format.extentp. 4528-4533
dc.language.isoeng
dc.relation.ispartofProceedings - 2022 IEEE International Conference on Big Data, Big Data 2022
dc.rights©,
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85147964326&doi=10.1109%2fBigData55660.2022.10020772&partnerID=40&md5=c1157330061beba75e6075f6243a59d8
dc.titleAi applications in forest monitoring need remote sensing benchmark datasets
dc.typeconference outputspa
dc.identifier.doi10.1109/BigData55660.2022.10020772
dc.relation.projectIDMU-21-UP2021_030
dc.relation.publisherversionhttp://dx.doi.org/10.1109/BigData55660.2022.10020772


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