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Testing feature selection in traffic signs

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Control, Aprendizaje y Optimización de Sistemas (CAOS)es
dc.contributor.authorSesmero Lorente, María Paz
dc.contributor.authorAlonso Weber, Juan Manuel
dc.contributor.authorGutiérrez Sánchez, Germán
dc.contributor.authorSanchis de Miguel, María Araceli
dc.date.accessioned2011-09-23T17:58:29Z
dc.date.available2011-09-23T17:58:29Z
dc.date.issued2007
dc.description.abstractRoad signs carry essential information for successful driving. Therefore, if we are interested in developing a Driver Support Systems, both, detection and classification of road signs are essential tasks for an autonomous system. However, both tasks are some of the less studied subjects in the field of Intelligent Transport systems. In this research we lay the foundations of a software implementation for a classifier system that will be implemented in hardware and will be able to be used for real-time traffic sign categorization. The selected classification method is a Multilayer Perceptron trained with Back-Propagation algorithm. The reason of this selection is, on one hand, that for certain types of problems, such as object recognition in natural environments, neural network learning methods provide a robust approach. On the other hand, and under certain, limitations related mainly to the number of units, a hardware implementation on FPGA of ANN is possible. Therefore, ANNs are a good method for real-time processing in real-word problems
dc.description.sponsorshipThis work has been supported by the Spanish Government under project TRA2004-07441-C03-C01
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationComputer aided systems theory (EUROCAST 2007): 11th International Conference on Computer Aided Systems Theory: Las Palmas de Gran Canaria, Spain, February 2007: extended abstracts. Las Palmas de Gran Canaria: Universidad, 2007, p. 396-398. ISBN 978-84-690-3603-7
dc.identifier.isbn978-84-690-3603-7
dc.identifier.publicationfirstpage396
dc.identifier.publicationlastpage398
dc.identifier.publicationtitleComputer aided systems theory (EUROCAST 2007): 11th International Conference on Computer Aided Systems Theory: Las Palmas de Gran Canaria, Spain, February 2007: extended abstracts
dc.identifier.urihttps://hdl.handle.net/10016/12177
dc.language.isospa
dc.publisherUniversidad de Las Palmas de Gran Canaria
dc.relation.eventdate2007
dc.relation.eventnumber11
dc.relation.eventplaceLas Palmas de Gran Canaria, España
dc.relation.eventtitleInternational Conference on Computer Aided Systems Theory, EUROCAST 2007
dc.rights.accessRightsopen access
dc.subject.ecienciaInformática
dc.subject.otherDriver support systems
dc.subject.otherIntelligent Transportation Systems
dc.subject.otherMultilayer perceptron
dc.subject.otherBackpropagation algorithm
dc.subject.otherFPGA (Field Programmable Gate Array)
dc.subject.otherANN
dc.titleTesting feature selection in traffic signs
dc.typeconference proceedings*
dc.type.hasVersionAM*
dspace.entity.typePublication
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