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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21b.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34P/3LKDP6L
Repositóriosid.inpe.br/mtc-m21b/2016/05.02.15.21   (acesso restrito)
Última Atualização2017:07.21.16.43.35 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21b/2016/05.02.15.21.15
Última Atualização dos Metadados2018:06.04.02.40.44 (UTC) administrator
DOI10.1080/2150704X.2016.1154218
ISSN2150-704X
Chave de CitaçãoNegriDutrSant:2016:CoSuVe
TítuloComparing support vector machine contextual approaches for urban area classification
Ano2016
MêsMay
Data de Acesso08 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho1781 KiB
2. Contextualização
Autor1 Negri, Rogério G.
2 Dutra, Luciano Vieira
3 Sant'Anna, Sidnei João Siqueira
Identificador de Curriculo1
2 8JMKD3MGP5W/3C9JHMA
3 8JMKD3MGP5W/3C9JJ8N
Grupo1
2 DPI-OBT-INPE-MCTI-GOV-BR
3 DPI-OBT-INPE-MCTI-GOV-BR
Afiliação1 Universidade Estadual Paulista (UNESP)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 rogerio.negri@ict.unesp.br
2 luciano.dutra@inpe.br
3 sidnei.santanna@inpe.br
RevistaRemote Sensing Letters
Volume7
Número5
Páginas485-494
Nota SecundáriaA2_GEOGRAFIA B2_INTERDISCIPLINAR B3_GEOCIÊNCIAS B4_CIÊNCIAS_AMBIENTAIS
Histórico (UTC)2016-05-02 15:21:15 :: simone -> administrator ::
2017-01-09 13:59:26 :: administrator -> simone :: 2016
2017-07-21 16:43:35 :: simone -> administrator :: 2016
2018-06-04 02:40:44 :: administrator -> simone :: 2016
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
ResumoSupport vector machine (SVM) has been receiving a great deal of attention for remote sensing data classification. Although the original formulation of this method does not incorporate contextual information, lately different formulations have been proposed to incorporate such information, with the aim of improving the mapping accuracy. In general, these proposals modify the SVM training phase or integrate the SVM classifications in stochastic models. Recently, two new contextual versions of SVM, context adaptive and competitive translative SVM (CaSVM and CtSVM, respectively), were proposed in literature. In this work, two case studies of urban area classification, using IKONOS-II and hyperspectral digital imagery collection experiment (HYDICE) data sets were conducted to compare SVM, SVM integrated with the iterated conditional modes (ICM) stochastic algorithm, SVM smoothed using the mode filter and the recent approaches CaSVM and CtSVM. The results indicated that although it possesses a high computational cost, the CaSVM method was able to produce classification results with similar accuracy (using kappa coefficient) to those obtained using SVM integrated with ICM (SVM+ICM) and the mode filter (SVM+Mode), all of them found statistically superior to the SVM result at 95% confidence level for the IKONOS-II image. For HYDICE image, all results were found statistically insignificant at 95% confidence level. Investigation of what happens at transition regions between classes, however, showed that some methods can present superior performance. To this objective, a new performance measure, called upsilon coefficient, was introduced in this work, which measures the impact that the smoothing effect, typical of contextual methods, can have in distorting the edges between regions. With this new measure was found that CaSVM is the one which has better performance followed with SVM+ICM.
ÁreaSRE
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4. Condições de acesso e uso
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Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Política de Arquivamentodenypublisher denyfinaldraft12
Permissão de Leituradeny from all and allow from 150.163
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhourlib.net/www/2011/03.29.20.55
Unidades Imediatamente Superiores8JMKD3MGPCW/3EQCCU5
Lista de Itens Citandosid.inpe.br/bibdigital/2013/09.09.15.05 3
sid.inpe.br/mtc-m21/2012/07.13.15.00.20 3
sid.inpe.br/mtc-m21/2012/07.13.14.53.50 1
DivulgaçãoWEBSCI; MGA; COMPENDEX; SCOPUS.
Acervo Hospedeirosid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notas
Campos Vaziosalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn keywords label lineage mark nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject targetfile tertiarymark tertiarytype url
7. Controle da descrição
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