Real-Time Traffic Sign Detection and Recognition using CNN

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dc.contributor.authorSantos, Daniel Castriani
dc.contributor.authorSilva, Francisco Assis Da
dc.contributor.authorPereira, Danillo Roberto
dc.contributor.authorAlmeida, Leandro Luiz De
dc.contributor.authorArtero, Almir Olivette [UNESP]
dc.contributor.authorPiteri, Marco Antonio [UNESP]
dc.contributor.authorAlbuquerque, Victor Hugo
dc.contributor.institutionPresidente Prudente
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de Fortaleza (Unifor)
dc.date.accessioned2020-12-12T02:40:27Z
dc.date.available2020-12-12T02:40:27Z
dc.date.issued2020-03-01
dc.description.abstractTraffic signs presents on streets and highways have a distinct set of features which may be used to differentiate each one from each other. We propose in this paper a real-time traffic sign detection and recognition algorithm using neural networks. In order to detect traffic sign we used a Faster R-CNN (Region-Based Convolutional Neural Network), and to classify we used a Convolutional Neural Network using two different architectures. Some factors can make it difficult, such as light, occlusion, blurring, and others. This work can be applied in several areas, such as Advanced Driving Assistant System and autonomous cars.en
dc.description.affiliationUniversidade Do Oeste Paulista (Unoeste) Presidente Prudente
dc.description.affiliationUniversidade Estadual Paulista (Unesp) Presidente Prudente
dc.description.affiliationUniversidade de Fortaleza (Unifor)
dc.description.affiliationUnespUniversidade Estadual Paulista (Unesp) Presidente Prudente
dc.format.extent522-529
dc.identifierhttp://dx.doi.org/10.1109/TLA.2020.9082723
dc.identifier.citationIEEE Latin America Transactions, v. 18, n. 3, p. 522-529, 2020.
dc.identifier.doi10.1109/TLA.2020.9082723
dc.identifier.issn1548-0992
dc.identifier.scopus2-s2.0-85084288646
dc.identifier.urihttp://hdl.handle.net/11449/201734
dc.language.isopor
dc.relation.ispartofIEEE Latin America Transactions
dc.sourceScopus
dc.subjectComputer Vision
dc.subjectConvolutional Neural Network
dc.subjectRegion-Based Convolutional Neural Network
dc.titleReal-Time Traffic Sign Detection and Recognition using CNNen
dc.typeArtigo
unesp.author.orcid0000-0003-4994-9914[2]
unesp.author.orcid0000-0001-7934-6482[3]
unesp.author.orcid0000-0003-3293-7386[4]
unesp.author.orcid0000-0001-6824-7251[5]
unesp.author.orcid0000-0003-3886-4309[7]
unesp.departmentMatemática e Computação - FCTpt

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Presidente Prudente - FCT - Faculdade de Ciências e Tecnologia