Facial recognition system for access control through Artificial Intelligence

• Autores: Reyes Campos, Jean Elias Manuel, Castañeda Rodríguez, Christian Stephano, Alva Luján, Luis Daniel, Mendoza de los Santos, Alberto Carlos
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Universidad La Salle
• Repositorio: Revistas - Universidad La Salle
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.ulasalle.edu.pe:article/78
• Enlace del recurso: https://revistas.ulasalle.edu.pe/innosoft/article/view/78; https://doi.org/10.48168/innosoft.s11.a78; https://purl.org/42411/s11/a78; https://n2t.net/ark:/42411/s11/a78
• Nivel de acceso: acceso abierto
• Materia: Access Control; Artificial Intelligence; Convolutional Neural Networks; Control de acceso; Inteligencia Artificial; Redes Neuronales Convolucionales

The main objective of this article is the development of a system that allows the facial recognition of a person for access control through Artificial Intelligence. For the development of the system, the Convolutional Neural Networks algorithm was used, which is a recognition model. Likewise, the Python programming language and the following libraries such as Numpy, Os, OpenCV and Imutils were used for its implementation. The results obtained according to the hit and using a dataset of 4500 images are approximately 88% in terms of the prediction per person, concluding that the recognition system is effective and has greater efficiency by increasing the size of datasets generated by individuals.