Reconocimiento óptico de números escritos a mano usando funciones de base radial y sistema memético diferencial
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Universidad Distrital Francisco José de Caldas
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El problema de reconocimiento óptico de números escritos a mano ha sido trabajado desde diferentes técnicas obteniendo buenos resultados. En el presente artículo se proponen sistemas difusos con algoritmos genéticos, más específicamente meméticos para realizar esta tarea. Los resultados obtenidos con este método son comparados con redes neuronales de aprendizaje semi-supervisado, donde fueron utilizadas redes con funciones de base radial (RBF). Al realizar la comparación es posible observar que este tipo de redes neuronales ofrecen ventajas en cuanto a tasas de error y tiempo de obtención del sistema de reconocimiento frente a los métodos basados en sistemas difusos.
Optical recognition of handwritten numbers was worked by different methods, with satisfactory results. In this paper, we propose fuzzy systems with genetic algorithms, specifically memetic, to do this task. Results with this method are compared with neuronal network of semi-supervised learning, where we was used networks with radial base functions (RBF). To make the comparison, is possible observed that this kind of neuronal network offers advantages regarding error rates and time-to-results of the recognition system, compared with methods based in fuzzy systems.
Optical recognition of handwritten numbers was worked by different methods, with satisfactory results. In this paper, we propose fuzzy systems with genetic algorithms, specifically memetic, to do this task. Results with this method are compared with neuronal network of semi-supervised learning, where we was used networks with radial base functions (RBF). To make the comparison, is possible observed that this kind of neuronal network offers advantages regarding error rates and time-to-results of the recognition system, compared with methods based in fuzzy systems.
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Differential evolution, Fuzzy modeling, mimetic algorithm, optical recognition of numbers, Radial Basis Function neural network, evolución diferencial, modelado difuso, algoritmo memético, reconocimiento óptico de números, redes neuronales de función de base radial