Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Manuel Oviedo-de La Fuente"'
Publikováno v:
Mathematics, Vol 9, Iss 12, p 1328 (2021)
Supervised classification of 3D point clouds using machine learning algorithms and handcrafted local features as covariates frequently depends on the size of the neighborhood (scale) around each point used to determine those features. It is therefore
Externí odkaz:
https://doaj.org/article/8ccb7f64f841447d92673bd5b3e2957e
Publikováno v:
Mathematics, Vol 8, Iss 6, p 941 (2020)
Predicting anomalous emission of pollutants into the atmosphere well in advance is crucial for industries emitting such elements, since it allows them to take corrective measures aimed to avoid such emissions and their consequences. In this work, we
Externí odkaz:
https://doaj.org/article/354a9bc5b73b4267b386fa7a7dcb4193
Publikováno v:
Kalpa Publications in Computing.
This work introduces a new approach in time-series analysis field for automatic co- variates selection in dynamic regression models. Based on [1] and [2] previous study, a forward-selection method is proposed for adding new significant covariates fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fe3b0e5f73e766c2195ae965db26563
https://doi.org/10.29007/1c23
https://doi.org/10.29007/1c23
Publikováno v:
PLoS ONE, Vol 13, Iss 3, p e0193651 (2018)
Influenza surveillance is critical to monitoring the situation during epidemic seasons and predictive mathematic models may aid the early detection of epidemic patterns. The objective of this study was to design a real-time spatial predictive model o
Externí odkaz:
https://doaj.org/article/17d2a02ecc094b7b89a718aba5f822ff
Publikováno v:
PLoS ONE, Vol 13, Iss 4, p e0194250 (2018)
This paper proposes a novel approach that uses meteorological information to predict the incidence of influenza in Galicia (Spain). It extends the Generalized Least Squares (GLS) methods in the multivariate framework to functional regression models w
Externí odkaz:
https://doaj.org/article/ade0283361b04df7a9da77065b8a634d
Publikováno v:
Mathematics in Industry ISBN: 9783030961725
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be2e7c6da70a7c5ac7e6a3b7c75d83f1
https://doi.org/10.1007/978-3-030-96173-2_10
https://doi.org/10.1007/978-3-030-96173-2_10
Publikováno v:
Functional and High-Dimensional Statistics and Related Fields ISBN: 9783030477554
Multiple scale machine learning algorithms using handcrafted features are among the most efficient methods for 3D point cloud supervised classification and segmentation. Despite their proven good performance, there are still some aspects that are not
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60ec42bc08677c885b998c55447951d5
https://doi.org/10.1007/978-3-030-47756-1_28
https://doi.org/10.1007/978-3-030-47756-1_28
Publikováno v:
Minerva: Repositorio Institucional de la Universidad de Santiago de Compostela
Universidad de Santiago de Compostela (USC)
Mathematics, Vol 8, Iss 941, p 941 (2020)
Investigo. Repositorio Institucional de la Universidade de Vigo
Universidade de Vigo (UVigo)
Scopus
RUO: Repositorio Institucional de la Universidad de Oviedo
Universidad de Oviedo (UNIOVI)
RUO. Repositorio Institucional de la Universidad de Oviedo
instname
Mathematics
Volume 8
Issue 6
Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Universidad de Santiago de Compostela (USC)
Mathematics, Vol 8, Iss 941, p 941 (2020)
Investigo. Repositorio Institucional de la Universidade de Vigo
Universidade de Vigo (UVigo)
Scopus
RUO: Repositorio Institucional de la Universidad de Oviedo
Universidad de Oviedo (UNIOVI)
RUO. Repositorio Institucional de la Universidad de Oviedo
instname
Mathematics
Volume 8
Issue 6
Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Predicting anomalous emission of pollutants into the atmosphere well in advance is crucial for industries emitting such elements, since it allows them to take corrective measures aimed to avoid such emissions and their consequences. In this work, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff72a115f3ec853a91d7829410701598
http://hdl.handle.net/10347/23639
http://hdl.handle.net/10347/23639
Publikováno v:
Journal of Statistical Software, Vol 51, Iss 4 (2012)
This paper is devoted to the R package fda.usc which includes some utilities for functional data analysis. This package carries out exploratory and descriptive analysis of functional data analyzing its most important features such as depth measuremen
Externí odkaz:
https://doaj.org/article/a227711733b64c5f8b858828f444f759
Publikováno v:
Mathematics, Vol 9, Iss 1328, p 1328 (2021)
RUC. Repositorio da Universidade da Coruña
instname
Scopus
Mathematics; Volume 9; Issue 12; Pages: 1328
RUO. Repositorio Institucional de la Universidad de Oviedo
Universidad de las Islas Baleares
RUC. Repositorio da Universidade da Coruña
instname
Scopus
Mathematics; Volume 9; Issue 12; Pages: 1328
RUO. Repositorio Institucional de la Universidad de Oviedo
Universidad de las Islas Baleares
[Abstract] Supervised classification of 3D point clouds using machine learning algorithms and handcrafted local features as covariates frequently depends on the size of the neighborhood (scale) around each point used to determine those features. It i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20793a2578172d0e64bccba68e506afd
https://doi.org/10.3390/math9121328
https://doi.org/10.3390/math9121328