Result: Feasibility Enterprise Time and Attendance System Using Artificial Vision Based on Neural Networks with Python and Raspberry Pi.
Further Information
El objetivo del presente artículo es el modelado de un sistema de reconocimiento facial, mediante la utilización de una Raspberry PI y Machine Learning (ML), para un sistema de control de asistencia. El aprendizaje de máquina o ML es una rama de la inteligencia artificial que permite el entrenamiento de algoritmos inspirados en sistemas biológicos, usando una cantidad considerable de información. En este trabajo, se ha usado la arquitectura de redes neuronales artificiales con retropropagación del error, las cuales guardan cierta similitud con las neuronas humanas y tienen la capacidad de extraer conocimiento a partir de los datos de entrada. Los algoritmos han sido implementados en Python y los resultados muestran una alta precisión para la clasificación y reconomiento de personas. The objective of this article is to model a facial recognition system, using a Raspberry PI and Machine Learning (ML), for an attendance control system. Machine learning is a branch of artificial intelligence that allows the training of algorithms inspired by biological systems, using a considerable amount of information. In this work, the architecture of artificial neural networks with error backpropagation has been used, which have a certain similarity with human neurons and can extract knowledge from the input data. The algorithms have been implemented in Python and the results show a high precision for the classification and recognition of people. [ABSTRACT FROM AUTHOR]
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