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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Repositorysid.inpe.br/sibgrapi@80/2007/08.01.19.41
Last Update2007:08.01.19.41.35 administrator
Metadatasid.inpe.br/sibgrapi@80/2007/08.01.19.41.37
Metadata Last Update2020:02.19.03.06.19 administrator
Citation KeySantosBati:2007:FeSeEq
TitleFeature selection with equalized salience measures and its application to segmentation
FormatPrinted, On-line.
Year2007
Access Date2021, Jan. 25
Number of Files1
Size1846 KiB
Context area
Author1 Santos, Davi Pereira dos
2 Batista, Joao
Affiliation1 ICMC - USP
2 ICMC - USP
EditorFalcão, Alexandre Xavier
Lopes, Hélio Côrtes Vieira
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
Conference LocationBelo Horizonte
DateOct. 7-10, 2007
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2007-08-01 19:41:37 :: jbatista@icmc.usp.br -> administrator ::
2007-08-02 21:17:48 :: administrator -> jbatista@icmc.usp.br ::
2008-07-17 14:09:43 :: jbatista@icmc.usp.br -> administrator ::
2009-08-13 20:38:29 :: administrator -> banon ::
2010-08-28 20:02:29 :: banon -> administrator ::
2020-02-19 03:06:19 :: administrator -> :: 2007
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Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsFeature Selection, texture, salience measures.
AbstractSegmentation is a crucial step in Computer Vision in which texture plays an important role. The existence of a large amount of methods from which texture can be computed is, sometimes, a hurdle to overcome when it comes to modeling solutions for texture-based segmentation. Following the excellence of the natural vision system and its generality, this work has adopted a feature selection method based on salience of synaptic connections of a Multilayer Perceptron neural network. Unlike traditional approaches, this paper introduces an equalization scheme to salience measures which contributed to significantly improve the selection of the most suitable features and, hence, yield better segmentation. The proposed method is compared with exhaustive search according to the Jeffrey-Matusita distance criterion. Segmentation for images of natural scenes has also been provided as a probable application of the method.
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data URLhttp://urlib.net/rep/sid.inpe.br/sibgrapi@80/2007/08.01.19.41
zipped data URLhttp://urlib.net/zip/sid.inpe.br/sibgrapi@80/2007/08.01.19.41
Languageen
Target FilePID458377.pdf
User Groupjbatista@icmc.usp.br
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Mirror Repositorydpi.inpe.br/banon-pc2@80/2006/08.30.19.27
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume

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