1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 6qtX3pFwXQZeBBx/vRT7J |
Repository | sid.inpe.br/banon/2002/10.24.10.32 |
Last Update | 2002:09.10.03.00.00 (UTC) administrator |
Metadata Repository | sid.inpe.br/banon/2002/10.24.10.32.25 |
Metadata Last Update | 2022:06.14.00.11.51 (UTC) administrator |
DOI | 10.1109/SIBGRA.2002.1167145 |
Citation Key | OliveiraJrCarvFreiSabo:2002:EvNNHM |
Title | Evaluating NN and HMM classifiers for handwritten word recognition |
Year | 2002 |
Access Date | 2024, May 02 |
Number of Files | 1 |
Size | 150 KiB |
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2. Context | |
Author | 1 Oliveira Junior, Jose Josemar de 2 Carvalho, Joao Marques de 3 Freitas, Cinthia Obladen de Almendra 4 Sabourin, Robert |
Editor | Gonçalves, Luiz Marcos Garcia Musse, Soraia Raupp Comba, João Luiz Dihl Giraldi, Gilson Dreux, Marcelo |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 15 (SIBGRAPI) |
Conference Location | Fortaleza, CE, Brazil |
Date | 10-10 Oct. 2002 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
Organization | SBC - 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 |
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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 |
Abstract | This 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 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2002 > Evaluating NN and... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Evaluating NN and... |
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/6qtX3pFwXQZeBBx/vRT7J |
zipped data URL | http://urlib.net/zip/6qtX3pFwXQZeBBx/vRT7J |
Language | en |
Target File | 79.pdf |
User Group | administrator |
Visibility | shown |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPEW34M/46QCSHP 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2022/05.01.04.11 6 sid.inpe.br/sibgrapi/2022/06.10.21.49 1 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Notes | The conference was held in Fortaleza, CE, Brazil, from October 7 to 10. |
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