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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3S49SBP
Repositorysid.inpe.br/sibgrapi/2018/10.22.22.38
Last Update2018:10.22.22.49.40 (UTC) whendell.magalhaes@arapiraca.ufal.br
Metadata Repositorysid.inpe.br/sibgrapi/2018/10.22.22.38.53
Metadata Last Update2022:05.18.22.18.34 (UTC) administrator
Citation KeyMagalhãesQueiCabr:2018:ClTeUs
TitleClassificação de texturas usando a métrica de centralidade closeness
FormatOn-line
Year2018
Access Date2024, Apr. 30
Number of Files1
Size712 KiB
2. Context
Author1 Magalhães, Whendell Feijó
2 Queiroz, Fabiane da Silva
3 Cabral, Raquel da Silva
Affiliation1 Universidade Federal de Alagoas - Campus Arapiraca
2 Universidade Federal de Alagoas - Centro de Ciências Agrárias
3 Universidade Federal de Alagoas - Campus Arapiraca
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
e-Mail Addresswhendell.magalhaes@arapiraca.ufal.br
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Conference LocationFoz do Iguaçu, PR, Brazil
Date29 Oct.-1 Nov. 2018
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeUndergraduate Work
History (UTC)2018-10-22 22:49:40 :: whendell.magalhaes@arapiraca.ufal.br -> administrator :: 2018
2022-05-18 22:18:34 :: administrator -> :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsredes complexas
classificação de texturas
centralidade closeness
AbstractIn this paper, we propose a method for automatic description and classification of image texture. The images are modeled as weighted directed graphs. We use the centrality measure closeness and in-degree to generate a feature vector that describes the texture information. To validate the method, we train a k- Nearest Neighbors classifier and compare the obtained results with the Co-occurrence Matrix and Local Binary Patterns texture description techniques. For the experiments, we use the public dataset, KTH-TIPS. The accuracy of the proposed method is 95,52% that overcome the compared techniques.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2018 > Classificação de texturas...
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Classificação de Texturas Usando a Métrica de Centralidade Closeness.pdf 22/10/2018 19:38 711.4 KiB 
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agreement.html 22/10/2018 19:38 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3S49SBP
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3S49SBP
Languagept
Target FileClassificação de Texturas Usando a Métrica de Centralidade Closeness.pdf
User Groupwhendell.magalhaes@arapiraca.ufal.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3RPADUS
Citing Item Listsid.inpe.br/sibgrapi/2018/09.03.20.37 9
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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