On the influence of Markovian models for contextual-based Optimum-Path Forest classification
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/168182 |
Resumo: | Contextual classification considers the information about a sample’s neighborhood to improve standard pixel-based classification approaches. In this work, we evaluated four different Markovian models for Optimum-Path Forest contextual classification considering land use recognition in remote sensing data. Some insights about the situations in which each of them should be applied are stated, as well as the idea behind them is explained. |
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Repositório Institucional da UNESP |
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On the influence of Markovian models for contextual-based Optimum-Path Forest classificationContextual classificationMarkov Random FieldsOptimum-Path ForestContextual classification considers the information about a sample’s neighborhood to improve standard pixel-based classification approaches. In this work, we evaluated four different Markovian models for Optimum-Path Forest contextual classification considering land use recognition in remote sensing data. Some insights about the situations in which each of them should be applied are stated, as well as the idea behind them is explained.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Federal University of São Carlos – UFSCar Department of Computer ScienceSão Paulo State University – UNESP Department of ComputingSão Paulo State University – UNESP Department of ComputingCNPq: 303182/2011-3CNPq: 470571/2013-6Universidade Federal de São Carlos (UFSCar)Universidade Estadual Paulista (Unesp)Osaku, D.Levada, A. L.M.Papa, J. P. [UNESP]2018-12-11T16:40:07Z2018-12-11T16:40:07Z2014-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject462-469Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8827, p. 462-469.1611-33490302-9743http://hdl.handle.net/11449/1681822-s2.0-84949143701Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)0,295info:eu-repo/semantics/openAccess2021-10-23T21:44:19Zoai:repositorio.unesp.br:11449/168182Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:17:56.261774Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
On the influence of Markovian models for contextual-based Optimum-Path Forest classification |
title |
On the influence of Markovian models for contextual-based Optimum-Path Forest classification |
spellingShingle |
On the influence of Markovian models for contextual-based Optimum-Path Forest classification Osaku, D. Contextual classification Markov Random Fields Optimum-Path Forest |
title_short |
On the influence of Markovian models for contextual-based Optimum-Path Forest classification |
title_full |
On the influence of Markovian models for contextual-based Optimum-Path Forest classification |
title_fullStr |
On the influence of Markovian models for contextual-based Optimum-Path Forest classification |
title_full_unstemmed |
On the influence of Markovian models for contextual-based Optimum-Path Forest classification |
title_sort |
On the influence of Markovian models for contextual-based Optimum-Path Forest classification |
author |
Osaku, D. |
author_facet |
Osaku, D. Levada, A. L.M. Papa, J. P. [UNESP] |
author_role |
author |
author2 |
Levada, A. L.M. Papa, J. P. [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Federal de São Carlos (UFSCar) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Osaku, D. Levada, A. L.M. Papa, J. P. [UNESP] |
dc.subject.por.fl_str_mv |
Contextual classification Markov Random Fields Optimum-Path Forest |
topic |
Contextual classification Markov Random Fields Optimum-Path Forest |
description |
Contextual classification considers the information about a sample’s neighborhood to improve standard pixel-based classification approaches. In this work, we evaluated four different Markovian models for Optimum-Path Forest contextual classification considering land use recognition in remote sensing data. Some insights about the situations in which each of them should be applied are stated, as well as the idea behind them is explained. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-01-01 2018-12-11T16:40:07Z 2018-12-11T16:40:07Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8827, p. 462-469. 1611-3349 0302-9743 http://hdl.handle.net/11449/168182 2-s2.0-84949143701 |
identifier_str_mv |
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8827, p. 462-469. 1611-3349 0302-9743 2-s2.0-84949143701 |
url |
http://hdl.handle.net/11449/168182 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 0,295 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
462-469 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129414730350592 |