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1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m16c.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP8W/3BTFEM5
Repositóriosid.inpe.br/mtc-m18/2012/05.18.13.17
Última Atualização2012:05.18.13.17.53 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m18/2012/05.18.13.17.53
Última Atualização dos Metadados2018:06.04.03.55.41 (UTC) administrator
ISBN978-85-17-00059-1
Chave de CitaçãoHappFeitStre:2012:AsOpMe
TítuloAssessment of optimization methods for automatic tunning of segmentation parameters
FormatoOn-line.
Ano2012
Data de Acesso20 maio 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho462 KiB
2. Contextualização
Autor1 Happ, Patrick
2 Feitosa, Raul
3 Street, Alexandre
Endereço de e-Mail do Autor1 patrick@ele.puc-rio.br
2 raul@ele.puc-rio.br
3 street)@ele.puc-rio.br
EditorFeitosa, Raul Queiroz
Costa, Gilson Alexandre Ostwald Pedro da
Almeida, Cláudia Maria de
Fonseca, Leila Maria Garcia
Kux, Hermann Johann Heinrich
Endereço de e-Mailwanderf@dsr.inpe.br
Nome do EventoInternational Conference on Geographic Object-Based Image Analysis, 4 (GEOBIA).
Localização do EventoRio de Janeiro
DataMay 7-9, 2012
Editora (Publisher)Instituto Nacional de Pesquisas Espaciais (INPE)
Cidade da EditoraSão José dos Campos
Páginas490-495
Título do LivroProceedings
OrganizaçãoInstituto Nacional de Pesquisas Espaciais (INPE)
Histórico (UTC)2012-05-18 13:17:53 :: wanderf@dsr.inpe.br -> administrator ::
2012-05-30 13:45:36 :: administrator -> wanderf@dsr.inpe.br :: 2012
2012-06-01 15:12:45 :: wanderf@dsr.inpe.br -> marciana :: 2012
2012-06-12 14:28:25 :: marciana -> seki@dsr.inpe.br :: 2012
2012-06-13 15:55:31 :: seki@dsr.inpe.br -> marciana :: 2012
2012-06-14 15:03:57 :: marciana -> administrator :: 2012
2018-06-04 03:55:41 :: administrator -> :: 2012
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Palavras-ChaveImage Segmentation
Parameter Adjustment
Optimization
Genetic Algorithm
Derivative-Free Optimization
ResumoThe image segmentation is a key step in the image classification process since its quality will directly affects the classification result. The quality measure of image segmentation has been widely discussed in image analysis leading to the development of different metrics in order to try to automate the process and replace the subjective analysis of a specialist. These metrics are also known as similarity metrics (or functions) and evaluate the segmentation outcome comparing it with a given image containing some reference objects and returning a numerical value that express the similarity between the result and the expected references. As the quality can be expressed by a metric, the problem lies in achieving a small similarity value. This task is related to the input segmentation parameters that vary according to the image features and the classes of objects of interest. Given that the relation between the parameters and the segmentation quality can not be formulated, this procedure is generally done by a trial and error process. To avoid misleading and time consuming, automatic parameter tuning are proposed using genetic algorithms. However, this solution tends to have a high computational cost and another several parameters to tune. This work compares this solution with some derivative-free optimization methods to present some alternatives that have smaller computational cost.
ÁreaSRE
TipoSegmentation
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreementnão têm arquivos
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGP8W/3BTFEM5
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP8W/3BTFEM5
Idiomaen
Arquivo Alvo131.pdf
Grupo de Usuáriosadministrator
wanderf@dsr.inpe.br
Visibilidadeshown
5. Fontes relacionadas
Repositório Espelhourlib.net/www/2011/03.29.20.55
Acervo Hospedeirosid.inpe.br/mtc-m18@80/2008/03.17.15.17
6. Notas
Campos Vaziosaffiliation archivingpolicy archivist callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition group issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor shorttitle sponsor tertiarymark tertiarytype url versiontype volume


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