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3D Point Cloud Semantic Segmentation through Functional Data Analysis
| dc.contributor.author | Oviedo de La Fuente, Manuel | |
| dc.contributor.author | Cabo Gómez, Carlos | |
| dc.contributor.author | Roca Pardiñas, Javier | |
| dc.contributor.author | Loudermilk, E. Louise | |
| dc.contributor.author | Ordóñez Galán, Celestino | |
| dc.date.accessioned | 2024-02-26T07:38:09Z | |
| dc.date.available | 2024-02-26T07:38:09Z | |
| dc.date.issued | 2023 | |
| dc.identifier.citation | Journal of Agricultural Biological and Environmental Statistics (2023); doi:10.1007/s13253-023-00567 | |
| dc.identifier.issn | 1085-7117 | |
| dc.identifier.issn | 1537-2693 | |
| dc.identifier.uri | https://hdl.handle.net/10651/71510 | |
| dc.description.sponsorship | This research/work was supported by MINECO, PID2020-113578RB-I00 MTM2017-82724-R and PID2020-116587GB-I00 grants, and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020-14 and Centro de Investigación del Sistema universitario de Galicia ED431G 2019/01), all of them through the ERDF. “CITIC, a Research Center accredited by the Galician University System, is funded by the ”Consellería de Cultura, Educación e Universidade of the Xunta de Galicia. It was also funded in part by the US Department of Defense’s Strategic Environmental Research and Development Program, project no. RC19-1119. We acknowledge Tall Timbers Research Station for their support, including Dr. Robertson and Pebble Hill Plantation. The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA or US Government determination or policy”. Carlos Cabo received funding from the UK Natural Environment Research Council (NE/T001194/1), and from the Spanish Government (Ministry of Universities) and the European Union (NextGenerationEU), within the project MU21-UP2021-030. | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Journal of Agricultural Biological and Environmental Statistics | |
| dc.rights | © 2023 The Author(s) | |
| dc.rights | CC Reconocimiento 4.0 Internacional | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.source | WOS:001064742200001 | |
| dc.title | 3D Point Cloud Semantic Segmentation through Functional Data Analysis | |
| dc.type | journal article | |
| dc.identifier.doi | 10.1007/s13253-023-00567-w | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113578RB-I00/ES/METODOS ESTADISTICOS FLEXIBLES EN CIENCIA DE DATOS PARA DATOS COMPLEJOS Y DE GRAN VOLUMEN: TEORIA Y APLICACIONES/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-82724-R/ES/INFERENCIA ESTADISTICA FLEXIBLE PARA DATOS COMPLEJOS DE GRAN VOLUMEN Y DE ALTA DIMENSION/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116587GB-I00/ES/DINAMICA COMPLEJA E INFERENCIA NO PARAMETRICA/ | |
| dc.relation.projectID | MU21-UP2021-030 | |
| dc.relation.publisherversion | https://doi.org/10.1007/s13253-023-00567-w | |
| dc.rights.accessRights | open access | |
| dc.type.hasVersion | VoR |
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