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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP5W34M/3GD3H5L
Repositorysid.inpe.br/mtc-m21b/2014/05.30.02.29.15   (restricted access)
Last Update2014:06.17.14.49.55 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21b/2014/05.30.02.29.16
Metadata Last Update2021:01.03.02.11.39 (UTC) administrator
DOI10.1016/j.isprsjprs.2013.11.004
ISSN0924-2716
Labelisi 2014-05 NegriDutrSiqu:2014:InSuVe
Citation KeyNegriDutrSant:2014:InSuVe
TitleAn innovative support vector machine based method for contextual image classification
Year2014
MonthJan.
Access Date2024, May 19
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size2357 KiB
2. Context
Author1 Negri, Rogerio Galante
2 Dutra, Luciano Vieira
3 Sant'Anna, Sidnei Joao Siqueira
Resume Identifier1
2 8JMKD3MGP5W/3C9JHMA
3 8JMKD3MGP5W/3C9JJ8N
Group1 DSA-CPT-INPE-MCTI-GOV-BR
2 DPI-OBT-INPE-MCTI-GOV-BR
3 DPI-OBT-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 renato.galante@cptec.inpe.br
2 dutra@dpi.inpe.br
3 sidnei@dpi.inpe.br
e-Mail Addressmarcelo.pazos@inpe.br
JournalISPRS Journal of Photogrammetry and Remote Sensing
Volume87
Pages241-248
Secondary MarkA1_GEOCIÊNCIAS A2_INTERDISCIPLINAR A2_CIÊNCIAS_AMBIENTAIS B1_BIODIVERSIDADE B1_ENGENHARIAS_IV C_CIÊNCIAS_AGRÁRIAS_I
History (UTC)2021-01-03 02:11:39 :: administrator -> marcelo.pazos@inpe.br :: 2014
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordsimage classification
contextual information
support vector machine
AbstractSeveral remote sensing studies have adopted the Support Vector Machine (SVM) method for image classification. Although the original formulation of the SVM method does not incorporate contextual information, there are different proposals to incorporate this type of information into it. Usually, these proposals modify the SVM training phase or make an integration of SVM classifications using stochastic models. This study presents a new perspective on the development of contextual SVMs. The main concept of this proposed method is to use the contextual information to displace the separation hyperplane, initially defined by the traditional SVM. This displaced hyperplane could cause a change of the class initially assigned to the pixel. To evaluate the classification effectiveness of the proposed method a case study is presented comparing the results with the standard SVM and the SVM post-processed by the mode (majority) filter. An ALOS/PALSAR image, PLR mode, acquired over an Amazon area was used in the experiment. Considering the inner area of test sites, the accuracy results obtained by the proposed method is better than SVM and similar to SVM post-processed by the mode filter. The proposed method, however, produces better results than mode post-processed SVM when considering the classification near the edges between regions. One drawback of the method is the computational cost of the proposed method is significantly greater than the compared methods.
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4. Conditions of access and use
Languageen
User Groupadministrator
marcelo.pazos@inpe.br
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Reader Groupadministrator
marcelo.pazos@inpe.br
Visibilityshown
Archiving Policydenypublisher denyfinaldraft24
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Linking8JMKD3MGP7W/3EEEGJP
Mirror Repositoryiconet.com.br/banon/2006/11.26.21.31
Next Higher Units8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/43SRC6S
Citing Item Listsid.inpe.br/bibdigital/2013/09.09.15.05 5
sid.inpe.br/mtc-m21/2012/07.13.15.00.20 3
sid.inpe.br/bibdigital/2021/01.03.02.10 2
DisseminationWEBSCI; PORTALCAPES; COMPENDEX; SCOPUS.
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject targetfile tertiarytype url
7. Description control
e-Mail (login)marcelo.pazos@inpe.br
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