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1. Identity statement
Reference TypeBook Section
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W/3KN3638
Repositorysid.inpe.br/plutao/2015/12.04.14.16   (restricted access)
Last Update2017:07.21.18.56.45 (UTC) simone
Metadata Repositorysid.inpe.br/plutao/2015/12.04.14.16.09
Metadata Last Update2024:01.08.12.45.22 (UTC) simone
ISBN9783319167268
Labellattes: 5142426481528206 4 BragaGoShCaPlPl:2015:NoMeRe
Citation KeyBragaGoShCaPlPl:2015:NoMeRe
TitleNonlinear method of reduction of dimensionality based on artificial neural network and hardware implementation
Year2015
Access Date2024, May 17
Secondary TypePRE LI
Number of Files1
Size1400 KiB
2. Context
Author1 Braga, Jose Renato Garcia
2 Gomes, Vitor Conrado Faria
3 Shiguemori, Elcio Hideki
4 Campos Velho, Haroldo Fraga de
5 Plaza, Antonio
6 Plaza, Javier
Resume Identifier1
2
3
4 8JMKD3MGP5W/3C9JHC3
Group1 CAP-COMP-SPG-INPE-MCTI-GOV-BR
2 CEA-CEA-INPE-MCTI-GOV-BR
3
4 LAC-CTE-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 jose.braga@inpe.br
2 vitor.gomes_indra@inpe.br
3
4 haroldo.camposvelho@inpe.br
EditorConstanda, C.
Kirsch, A.
Book TitleIntegral methods in science and engineering: theoretical and computational advances
PublisherBirkhäuse
CityNew York (USA)
Pages69-79
History (UTC)2015-12-04 14:16:09 :: lattes -> administrator ::
2015-12-07 11:19:29 :: administrator -> simone :: 2015
2015-12-11 15:11:39 :: simone -> administrator :: 2015
2016-06-04 01:09:14 :: administrator -> simone :: 2015
2017-07-21 18:56:45 :: simone -> administrator :: 2015
2022-03-17 16:24:04 :: administrator -> simone :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsImage classification
Associative neural network
Artificial neural network
MPCA: multi-particle collision algorithm
Neural network self-configuring
AbstractHyper-spectral images present new applications, but they represent new challenges: data high dimension is one of them. Thus, it is important to develop new techniques for reducing the dimensionality of the data without loss of information. Therefore in this chapter, we conducted tests on a new dimensionality reduction method of data as well as its implementation in hardware.
AreaCOMP
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Nonlinear method of...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > CGCEA > Nonlinear method of...
Arrangement 3urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CAP > Nonlinear method of...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target File[Christian_Constanda,_Andreas_Kirsch]_Integral_Met(b-ok.org).pdf
User Grouplattes
Reader Groupadministrator
simone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3ESGTTP
8JMKD3MGPCW/3EU2FR5
8JMKD3MGPCW/3F2PHGS
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.49.40 3
sid.inpe.br/bibdigital/2013/09.22.23.14 2
sid.inpe.br/bibdigital/2013/10.01.23.29 1
URL (untrusted data)http://www.springer.com/us/book/9783319167268
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notes
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