1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 6qtX3pFwXQZeBBx/wpAPK |
Repository | sid.inpe.br/banon/2002/12.09.10.27 |
Last Update | 2002:11.28.02.00.00 (UTC) administrator |
Metadata Repository | sid.inpe.br/banon/2002/12.09.10.27.33 |
Metadata Last Update | 2022:06.14.00.12.32 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2001.963077 |
Citation Key | OliveiraBenSabBorSue:2001:FeSuSe |
Title | Feature subset selection using genetic algorithms for handwritten digit recognition |
Year | 2001 |
Access Date | 2024, Apr. 29 |
Number of Files | 1 |
Size | 605 KiB |
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2. Context | |
Author | 1 Oliveira, L. S. 2 Benahmed, N. 3 Sabourin, R. 4 Bortolozzi, F. 5 Suen, C. Y. |
Editor | Borges, Leandro Díbio Wu, Shin-Ting |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 14 (SIBGRAPI) |
Conference Location | Florianópolis, SC, Brazil |
Date | 15-18 Oct. 2001 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Pages | 362-369 |
Book Title | Proceedings |
Tertiary Type | Full Paper |
Organization | SBC - Brazilian Computer Society |
History (UTC) | 2008-07-17 14:10:55 :: administrator -> banon :: 2008-08-26 15:22:04 :: banon -> administrator :: 2009-08-13 20:37:23 :: administrator -> banon :: 2010-08-28 20:00:14 :: banon -> administrator :: 2022-06-14 00:12:32 :: administrator -> :: 2001 |
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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 subset selection genetic algorithms handwritten digit recognition |
Abstract | In this paper two approaches of genetic algorithm for feature subset selection are compared. The first approach considers a simple genetic algorithm (SGA) while the second one takes into account an iterative genetic algorithm (IGA) which is claimed to converge faster than SGA. Initially, we present an overview of the system to be optimized and the methodology applied in the experiments as well. Afterwards we discuss the advantages and drawbacks of each approach based on the experiments carried out on NIST SD19. Finally, we conclude that the IGA converges faster than the SGA, however, the SGA seems more suitable for our problem. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2001 > Feature subset selection... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Feature subset selection... |
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/wpAPK |
zipped data URL | http://urlib.net/zip/6qtX3pFwXQZeBBx/wpAPK |
Language | en |
Target File | 362-369.pdf |
User Group | administrator |
Visibility | shown |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPEW34M/46Q6TJ5 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2022/04.29.19.35 9 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Notes | The conference was held in Florianópolis, SC, Brazil, from October 15 to 18. |
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