Object localisation and tracking through subsymbolic classification

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorVieira Neto, Hugo-
Autor(es): dc.creatorNehmzow, Ulrich-
Data de aceite: dc.date.accessioned2025-08-29T12:27:34Z-
Data de disponibilização: dc.date.available2025-08-29T12:27:34Z-
Data de envio: dc.date.issued2013-11-28-
Data de envio: dc.date.issued2003-
Fonte completa do material: dc.identifierhttp://repositorio.utfpr.edu.br/jspui/handle/1/663-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1095721-
Descrição: dc.descriptionThis paper presents results of experiments in subsymbolic processing of visual data, to achieve identification and tracking of arbitrary objects, which are intended to be used in autonomous robots for novelty detection and navigation purposes. Artificial neural networks with unsupervised training are used as the classification stage for the vision system, in order to provide the robot the ability to develop its own representations from perceptual data without the need of any external human-provided information. We present an evaluation of the behaviour of the system when using very simple feature extraction techniques, such as horizontal and vertical average histograms, as well as average coarse coding.-
Descrição: dc.description5000-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherCuritiba-
Relação: dc.relationSymposium on Biologically-Inspired Machine Vision, Theory and Application-
Relação: dc.relationhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.5.6253&rep=rep1&type=pdf-
Palavras-chave: dc.subjectRobôs móveis-
Palavras-chave: dc.subjectVisão por computador-
Palavras-chave: dc.subjectRedes neurais (Computação)-
Palavras-chave: dc.subjectMobile robots-
Palavras-chave: dc.subjectComputer vision-
Palavras-chave: dc.subjectNeural networks (Computer science)-
Título: dc.titleObject localisation and tracking through subsymbolic classification-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositorio Institucional da UTFPR - RIUT

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