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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3DDQLDL
Repositorysid.inpe.br/sibgrapi/2013/01.21.16.33
Last Update2013:01.21.16.33.41 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2013/01.21.16.33.42
Metadata Last Update2022:06.17.04.32.55 (UTC) administrator
ISBN978-85-7669-272-0
Citation KeyBorgesOrrFish:1994:RaBaFu
TitleA radial basis function neural network for parts identification of three dimensional shapes
FormatImpresso, On-line.
Year1994
Access Date2024, Apr. 28
Number of Files1
Size5229 KiB
2. Context
Author1 Borges, Díbio Leandro
2 Orr, Mark J.
3 Fisher, Robert B.
Affiliation1 Department of Artificial Intelligence of Edinburgh University
2 Centre for Cognitive Science of Edinburgh University
3 Centre for Cognitive Science of Edinburgh University
EditorFreitas, Carla dal Sasso
Geus, Klaus de
Scheer, Sérgio
e-Mail Addresscintiagraziele.silva@gmail.com
Conference NameSimpósio Brasileiro de Computação Gráfica e Processamento de Imagens, 7 (SIBGRAPI)
Conference LocationCuritiba, PR, Brazil
Date9-11 Nov. 1994
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Volume1
Pages77-84
Book TitleAnais
Tertiary TypeArtigo
History (UTC)2013-01-21 16:33:42 :: cintiagraziele.silva@gmail.com -> administrator ::
2022-06-17 04:32:55 :: administrator -> cintiagraziele.silva@gmail.com :: 1994
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsfunction neural
function neural
image understanding
AbstractThis discrimination of volumetric pieces or parts of objects from range data is one key element for achieving 3-D object recognition. In this paper it is shown that previously segmented and acquired super quadrics from range data can be reliably mapped into a set of qualitative volumetric shapes (geons) by means of an RBF (Radial Basis Function) neural network classifier. We use a regularized RBF classifier and the results are shown to be both reliable and efficient in the context of range image understanding.
TypeVisão Computacional
Arrangement 1urlib.net > SDLA > Fonds > Full Index > A radial basis...
Arrangement 2urlib.net > SDLA > Fonds > SIBGRAPI 1994 > Sumário > A radial basis...
Arrangement 3urlib.net > SDLA > Fonds > SIBGRAPI 1994 > Sumário > Índice > A radial basis...
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/8JMKD3MGPBW34M/3DDQLDL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3DDQLDL
Languageen
Target File11 A radial basis function neural network.pdf
User Groupadministrator
cintiagraziele.silva@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/sibgrapi@80/2007/08.02.16.22
Next Higher Units8JMKD3MGPEW34M/4742MCS
8JMKD3MGPBW34M/3DFJRQE
8JMKD3MGPBW34M/3DG53A8
Citing Item Listsid.inpe.br/sibgrapi/2013/02.01.16.05 1
sid.inpe.br/sibgrapi/2013/02.04.16.04 1
sid.inpe.br/banon/2001/03.30.15.38.24 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group issn label lineage mark nextedition notes numberofvolumes orcid organization parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark url versiontype
7. Description control
e-Mail (login)cintiagraziele.silva@gmail.com
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