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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZeBBx/vRT7J
Repositorysid.inpe.br/banon/2002/10.24.10.32
Last Update2002:09.10.03.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/banon/2002/10.24.10.32.25
Metadata Last Update2022:06.14.00.11.51 (UTC) administrator
DOI10.1109/SIBGRA.2002.1167145
Citation KeyOliveiraJrCarvFreiSabo:2002:EvNNHM
TitleEvaluating NN and HMM classifiers for handwritten word recognition
Year2002
Access Date2024, May 02
Number of Files1
Size150 KiB
2. Context
Author1 Oliveira Junior, Jose Josemar de
2 Carvalho, Joao Marques de
3 Freitas, Cinthia Obladen de Almendra
4 Sabourin, Robert
EditorGonçalves, Luiz Marcos Garcia
Musse, Soraia Raupp
Comba, João Luiz Dihl
Giraldi, Gilson
Dreux, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 15 (SIBGRAPI)
Conference LocationFortaleza, CE, Brazil
Date10-10 Oct. 2002
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
OrganizationSBC - Brazilian Computer Society
History (UTC)2008-07-17 14:10:47 :: administrator -> banon ::
2008-08-26 15:21:22 :: banon -> administrator ::
2009-08-13 20:36:41 :: administrator -> banon ::
2010-08-28 20:00:07 :: banon -> administrator ::
2022-06-14 00:11:51 :: administrator -> :: 2002
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
AbstractThis paper evaluates NN and HMM classifiers applied to the handwritten word recognition problem. The goal is analyse the individual and combined performance of these classifiers. They are evaluated considering two different combination strategies and the experiments are performed with the same database and similar feature sets. The strategy proposed takes advantage of the different but complementary mechanisms of NN and HMM to obtain a more efficient hybrid classifier. The recognition rates obtained vary from 75.9% using the HMM classifier alone to 90.4% considering the NN and HMM combination.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2002 > Evaluating NN and...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Evaluating NN and...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZeBBx/vRT7J
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZeBBx/vRT7J
Languageen
Target File79.pdf
User Groupadministrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46QCSHP
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.01.04.11 6
sid.inpe.br/sibgrapi/2022/06.10.21.49 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
NotesThe conference was held in Fortaleza, CE, Brazil, from October 7 to 10.
Empty Fieldsaffiliation archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress edition electronicmailaddress format group isbn issn keywords label lineage mark mirrorrepository nextedition numberofvolumes orcid 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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