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http://reini.utcv.edu.mx:80/handle/123456789/1416
Título : | Recognition Module for the Identification and Classification of Patterns in Vehicles Using Deep Learning Techniques |
Autor : | Saira Carolina Castañeda Heredia Marlen Fructuoso Bravo Miguel Ángel Flores Nestlé Yazmín Saavedra Zárate Ricardo Castro Valdivia Luis Rolando Guarneros Nolasco |
Palabras clave : | Artículo |
Fecha de publicación : | nov-2023 |
Editorial : | Universidad Nacional Autonoma de México |
Resumen : | In Mexico, vehicle theft is a serious problem that affects a considerable number of citizens. In the state of Veracruz, 61,796 cars have been reported stolen in one year. This paper presents a pattern recognition system using Artificial Intelligence techniques. This system uses video image analysis and a Deep Learning module to classify vehicles into two categories: automobiles and motorcycles. A case study used video surveillance cameras to capture more than 1,000 vehicles. The Deep Learning model achieved 85% classification accuracy. This solution will improve the identification of suspicious and stolen cars, contributing to security and traffic control. |
metadata.dc.identifier.*: | http://reini.utcv.edu.mx:80/handle/123456789/1416 |
metadata.dc.language: | spa |
Aparece en las colecciones: | Artículos arbitrados |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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24-Recognition-Module-for-the-Identification-and.pdf | 403.32 kB | Adobe PDF | Visualizar/Abrir |
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