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Listar por autor "Ortega-Zamorano, Francisco"
Mostrando ítems 1-4 de 4
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Algoritmos de aprendizaje neurocomputacionales para su implementación hardware
Ortega-Zamorano, Francisco (Servicio de Publicaciones y Divulgación Científica, 2015)Las redes de neuronas artificiales son un paradigma de aprendizaje y procesamiento automático inspirado en el funcionamiento del sistema nervioso, se emplean en toda tipo de aplicaciones, con lo que van apareciendo nuevas ... -
Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences
Palomo-Ferrer, Esteban José; Benito-Picazo, Jesús; Domínguez-Merino, Enrique
; López-Rubio, Ezequiel
; Ortega-Zamorano, Francisco (Springer, 2021-09)
In this paper, a new color quantization method based on a self-organized artificial neural network called the Growing Hierarchical Bregman Neural Gas (GHBNG) is proposed. This neural network is based on Bregman divergences, ... -
Smart motion detection sensor based on video processing using self-organizing maps
Ortega-Zamorano, Francisco; Molina-Cabello, Miguel Ángel; López-Rubio, Ezequiel
; Palomo-Ferrer, Esteban José
(Elsevier, 2016)
Most current approaches to computer vision are based on expensive, high performance hardware to meet the heavy computational requirements of the employed algorithms. These system architectures are severely limited in their ... -
Solving Scheduling Problems with Genetic Algorithms using a Priority Encoding Scheme
Subirats, J.L.; Mesa, Héctor; Ortega-Zamorano, Francisco; Juárez, G.E.; Jerez-Aragonés, José Manuel; Turias, Ignacio; Franco, Leonardo[et al.] (2017-06-26)
Scheduling problems are very hard computational tasks with several applications in multitude of domains. In this work we solve a practical problem motivated by a real industry situation, in which we apply a genetic algorithm ...