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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZeBBx/DcAw2
Repositorysid.inpe.br/banon/2004/08.19.00.32
Last Update2004:08.19.03.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/banon/2004/08.19.00.32.37
Metadata Last Update2022:06.14.00.12.48 (UTC) administrator
DOI10.1109/SIBGRA.2004.1352947
Citation KeyOliveiraJúniorKapFreCarSab:2004:HaReMu
TitleHandwritten Recognition with Multiple Classifiers for Restricted Lexicon
FormatOn-line
Year2004
Access Date2024, May 02
Number of Files1
Size275 KiB
2. Context
Author1 Oliveira Júnior, José Josemar
2 Kapp, Marcelo Nepomoceno
3 Freitas, Cinthia Obladen de Almendra
4 Carvalho, João Marques de
5 Sabourin, Robert
Affiliation1 Universidade Federal de Campina Grande, Coordenação de Pós-Graduação em Engenharia Elétrica, Caixa Postal 10105, 58109-970, Campina Grande, PB - Brazil
2 Pontíficia Universidade Católica do Paraná, R. Imaculada Conceição 1155, 80215-901, Curitiba, PR - Brazil
3 Ècole de Technologie Superieure, 1100 Rue Notre Dame Ouest, H3C 1K3, Montreal, QC - Canada
EditorAraújo, Arnaldo de Albuquerque
Comba, João Luiz Dihl
Navazo, Isabel
Sousa, Antônio Augusto de
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 17 (SIBGRAPI) - Ibero-American Symposium on Computer Graphics, 2 (SIACG)
Conference LocationCuritiba, PR, Brazil
Date17-20 Oct. 2004
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2008-07-17 14:10:57 :: josemar -> banon ::
2008-08-26 15:15:44 :: banon -> administrator ::
2009-08-13 20:37:37 :: administrator -> banon ::
2010-08-28 20:01:15 :: banon -> administrator ::
2022-06-14 00:12:48 :: administrator -> :: 2004
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordspattern recognition
multiple classifiers
handwritten recognition
AbstractThis paper prsents a multiple classifier system applied to the handwritten word recognition (HWR) problem. The goal is to analyse the influence of different global classifiers taken isolatedly as well as combined in a particular HWR task. The application proposed is the recognition of the Portuguese handwritten names of the months. The strategy takes advantage of the complementarity mechanisms of three different classifiers: Conventional Neural Network, Class-Modular Neural Network and Hidden Markov Models, yielding a multiple classifier that is more efficient than either individual technique. The recognition rates obtained vary from 75.9% using the stand alone HMM classifier to 96.0% considering the classifiers combination.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2004 > Handwritten Recognition with...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Handwritten Recognition with...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZeBBx/DcAw2
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZeBBx/DcAw2
Languageen
Target File4382_oliveira_jose.pdf
User Groupjosemar
administrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46QM2BE
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.03.00.29 10
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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