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dc.contributor.advisorMartínez-Sánchez, Víctor H.
dc.contributor.authorVázquez-Espinoza, Carlos S.
dc.date.accessioned2023-05-09T20:20:25Z
dc.date.accessioned2024-02-27T18:49:05Z
dc.date.available2023-05-09T20:20:25Z
dc.date.available2024-02-27T18:49:05Z
dc.date.issued2023-05
dc.identifier.citationVázquez-Espinoza, C. S. (2023). Traffic Sign Detection and Recognition with Voice Assistant. Trabajo de obtención de grado, Maestría en Sistemas Computacionales. Tlaquepaque, Jalisco: ITESO.es_MX
dc.identifier.urihttps://hdl.handle.net/20.500.12032/122346
dc.descriptionhere are multitude of applications for detection and recognition of images across different fields. There are some specific applications for these systems used to help people to drive for example in autonomous driving as well as other applications. There has been another focus in the use of classification models used to help drivers providing details about their surrounding while driving. In places like Guadalajara, such models are a valuable tool to reduce traffic accidents. This document will explain the development of a detection and recognition of traffic signs model. This model has the intention of providing details about the meaning of the traffic signs. All this will happen close to real time and will be an additional information to the driver. This whole system could be used by anyone but specifically aimed to people with visual deficiencies. With the use of a robust machine learning and the use of Deep Learning (DL), the expectative is to achieve high accuracy levels on the traffic sign detection and recognition. This system is expected to be available and affordable for most of the drivers in Guadalajara.es_MX
dc.description.sponsorshipITESO, A. C.es
dc.language.isoenges_MX
dc.publisherITESOes_MX
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes_MX
dc.subjectMachine Learninges_MX
dc.subjectDeep Learninges_MX
dc.titleTraffic Sign Detection and Recognition with Voice Assistantes_MX
dc.typeinfo:eu-repo/semantics/masterThesises_MX


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