Relevant Traffic Light Recognition with Deep Learning Approaches

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dc.contributor.advisor1Santos, Thiago Oliveira dos
dc.contributor.advisor1IDhttps://orcid.org/
dc.contributor.advisor1Latteshttp://lattes.cnpq.br/5117339495064254
dc.contributor.authorFreitas, Rafael Horimoto de
dc.contributor.authorIDhttps://orcid.org/
dc.contributor.authorLatteshttp://lattes.cnpq.br/
dc.contributor.referee1Goncalves, Claudine Santos Badue
dc.contributor.referee1IDhttps://orcid.org/
dc.contributor.referee1Latteshttp://lattes.cnpq.br/1359531672303446
dc.contributor.referee2Ciarelli, Patrick Marques
dc.contributor.referee2IDhttps://orcid.org/0000000331774028
dc.contributor.referee2Latteshttp://lattes.cnpq.br/1267950518719423
dc.date.accessioned2024-05-30T00:48:40Z
dc.date.available2024-05-30T00:48:40Z
dc.date.issued2019-10-22
dc.description.abstractSelf-driving cars have the important task of recognizing the state (e.g., red, green, or yellow) of the traffic lights that are relevant, i.e., that define guidance to the car. Common approaches consist of using the image captured from a forward-looking c
dc.description.resumoCarros autônomos têm a importante tarefa de reconhecer o estado (e.g., vermelho, verde, ou amarelo) dos semáforos que são relevantes, i.e., que definem orientação para o carro. Abordagens comuns consistem em usar a imagem capturada de uma câmera prospecti
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.formatText
dc.identifier.urihttps://dspace5.ufes.br/handle/10/13835
dc.languagepor
dc.publisherUniversidade Federal do Espírito Santo
dc.publisher.countryBR
dc.publisher.courseMestrado em Informática
dc.publisher.departmentCentro Tecnológico
dc.publisher.initialsUFES
dc.publisher.programPrograma de Pós-Graduação em Informática
dc.rightsopen access
dc.subjectPalavra-chave
dc.subject.br-rjbnsubject.br-rjbn
dc.subject.cnpqCiência da Computação
dc.titleRelevant Traffic Light Recognition with Deep Learning Approaches
dc.title.alternativeRelevant Traffic Light Recognition with Deep Learning Approaches
dc.typemasterThesis

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