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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZeBBx/GFSRc
Repositorysid.inpe.br/banon/2005/07.07.18.38
Last Update2005:07.12.03.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/banon/2005/07.07.18.38.42
Metadata Last Update2022:06.14.00.12.55 (UTC) administrator
DOI10.1109/SIBGRAPI.2005.19
Citation KeyBrevePontMasc:2005:CoMeSt
TitleCombining methods to stabilize and increase performance of neural network-based classifiers
FormatOn-line
Year2005
Access Date2024, May 03
Number of Files1
Size335 KiB
2. Context
Author1 Breve, Fabricio Aparecido
2 Ponti Junior, Moacir Pereira
3 Mascarenhas, Nelson Delfino d'Ávila
Affiliation1 Departamento de Computação – Universidade Federal de São Carlos, São Paulo, SP, Brasil
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
e-Mail Addressfbreve@gmail.com
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal, RN, Brazil
Date9-12 Oct. 2005
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2008-07-17 14:10:59 :: fbreve -> banon ::
2008-08-26 15:17:01 :: banon -> administrator ::
2009-08-13 20:37:45 :: administrator -> banon ::
2010-08-28 20:01:17 :: banon -> administrator ::
2022-06-14 00:12:55 :: administrator -> :: 2005
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsclassifier combining neural networks multilayer perceptron dempster-shafer decision templates bagging pattern recognition soil science tomography
AbstractIn this paper we present a set of experiments in order to recognize materials in multispectral images, which were obtained with a tomograph scanner. These images were classified by a neural network based classifier (Multilayer Perceptron) and classifier combining techniques (Bagging, Decision Templates and Dempster-Shafer) were investigated. We also present a performance comparison between the individual classifiers and the combiners. The results were evaluated by the estimated error (obtained using the Hold-Out technique) and the Kappa coefficient, and they showed performance stabilization.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2005 > Combining methods to...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Combining methods to...
doc Directory Contentaccess
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZeBBx/GFSRc
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZeBBx/GFSRc
Languageen
Target Filefbreve_combining.pdf
User Groupfbreve
administrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46R3ED5
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.05.04.08 6
sid.inpe.br/banon/2001/03.30.15.38.24 2
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage 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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