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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZG2LgkFdY/R28GU
Repositorysid.inpe.br/sibgrapi@80/2007/08.01.19.41
Last Update2007:08.01.19.41.35 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi@80/2007/08.01.19.41.37
Metadata Last Update2022:06.14.00.13.37 (UTC) administrator
DOI10.1109/SIBGRAPI.2007.17
Citation KeySantosBati:2007:FeSeEq
TitleFeature selection with equalized salience measures and its application to segmentation
FormatPrinted, On-line.
Year2007
Access Date2024, Apr. 26
Number of Files1
Size1846 KiB
2. Context
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, MG, Brazil
Date7-10 Oct. 2007
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2007-08-01 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 ::
2022-06-14 00:13:37 :: administrator -> :: 2007
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
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.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2007 > Feature selection with...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Feature selection with...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/R28GU
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/R28GU
Languageen
Target FilePID458377.pdf
User Groupjbatista@icmc.usp.br
administrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46SF8Q5
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.14.00.14 3
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress edition electronicmailaddress group isbn issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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