Sistema biométrico para el control de acceso a la UDIV de Desarrollo Computacional de la ESPAM-MFL empleando técnicas de Deep Learning

In this degree work, a biometric access control system was developed through the use of Deep Learning techniques focused on facial recognition with the express purpose of being implemented in the UDIV of Computational Development as a security system; first, a requirements gathering was carried out through an interview with the main head of the area about the security on site and any type of existing precedents, producing a document under the IEEE 890-1998 standard, the development and correct design of the fundamental parts of the system was carried out then, such as the artificial intelligence that will be in charge of receiving the data from the surveillance camera and interpreting them, all this following the CRISP-DM methodology, a database to manage the information and a graphical user interface that allows an optimal and understandable user experience through the use of Xtreme Programming (XP), amongst the principal results It was evident a precision of 98% in the face recognition model thanks to the obtained data from the workers for its usage in the aforementioned and a report module that showcases the different access schedules of employees

• Hlavní autor: Muñoz Ríos, Lelis Javier (author)
• Další autoři: Ponce Almeida, Julio Josue (author)
• Médium: bachelorThesis
• Jazyk: spa
• Vydáno: 2024
• Témata: Control de acceso; Sistema biométrico; Seguridad; Deep Learning; Reconocimiento facial; Inteligencia artificial
• On-line přístup: http://repositorio.espam.edu.ec/handle/42000/2349