dc.creatorSilva,Romuere
dc.creatorAires,Kelson
dc.creatorVeras,Rodrigo
dc.creatorSantos,Thiago
dc.creatorLima,Kalyf
dc.creatorSoares,André
dc.date2013-12-01
dc.date.accessioned2023-09-25T18:35:17Z
dc.date.available2023-09-25T18:35:17Z
dc.identifierhttp://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002013000300004
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8838463
dc.descriptionMotorcycle accidents have been rapidly growing throughout the years in many countries. Due to various social and economic factors, this type of vehicle is becoming increasingly popular. Over the past years, automated mechanisms to inspect traffic violations such as radars and surveillance cameras are being used ever more. This paper’s goals are the study and implementation of some methods for automatic detection of motorcycles on public roads. Traffic images captured by cameras were used. For feature extraction of images, the algorithms SURF, HAAR, HOG and LBP were used as descriptors. For image classification, Multilayer Perceptron, Support Vector Machines and Radial-Bases Function Networks were used as classifiers. Finally, the results are presented and discussed
dc.formattext/html
dc.languageen
dc.publisherCentro Latinoamericano de Estudios en Informática
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceCLEI Electronic Journal v.16 n.3 2013
dc.subjectClassification
dc.subjectMotorcycle
dc.subjectMachine Learn
dc.titleAutomatic Motorcycle Detection on Public Roads
dc.typeinfo:eu-repo/semantics/article


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