1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 6qtX3pFwXQZG2LgkFdY/R28GU |
Repository | sid.inpe.br/sibgrapi@80/2007/08.01.19.41 |
Last Update | 2007:08.01.19.41.35 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi@80/2007/08.01.19.41.37 |
Metadata Last Update | 2022:06.14.00.13.37 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2007.17 |
Citation Key | SantosBati:2007:FeSeEq |
Title | Feature selection with equalized salience measures and its application to segmentation |
Format | Printed, On-line. |
Year | 2007 |
Access Date | 2025, Jan. 25 |
Number of Files | 1 |
Size | 1846 KiB |
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2. Context | |
Author | 1 Santos, Davi Pereira dos 2 Batista, Joao |
Affiliation | 1 ICMC - USP 2 ICMC - USP |
Editor | Falcão, Alexandre Xavier Lopes, Hélio Côrtes Vieira |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI) |
Conference Location | Belo Horizonte, MG, Brazil |
Date | 7-10 Oct. 2007 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full 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 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | Feature Selection texture salience measures |
Abstract | Segmentation 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 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2007 > Feature selection with... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Feature selection with... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/R28GU |
zipped data URL | http://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/R28GU |
Language | en |
Target File | PID458377.pdf |
User Group | jbatista@icmc.usp.br administrator |
Visibility | shown |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPEW34M/46SF8Q5 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2022/05.14.00.14 31 sid.inpe.br/sibgrapi/2022/06.10.21.49 5 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy 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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