E
Ezequiel López-Rubio
Researcher at University of Málaga
Publications - 173
Citations - 1675
Ezequiel López-Rubio is an academic researcher from University of Málaga. The author has contributed to research in topics: Artificial neural network & Convolutional neural network. The author has an hindex of 19, co-authored 155 publications receiving 1333 citations. Previous affiliations of Ezequiel López-Rubio include National University of Distance Education & ETSI.
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Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
Juan Manuel Górriz,Juan Manuel Górriz,Javier Ramírez,Andrés Ortiz,Francisco Jesús Martínez-Murcia,Fermín Segovia,John Suckling,Matthew Leming,Yudong Zhang,José Ramón Álvarez-Sánchez,Guido Bologna,Paula Bonomini,Fernando E. Casado,David Charte,Francisco Charte,Ricardo Contreras,Alfredo Cuesta-Infante,Richard J. Duro,Antonio Fernández-Caballero,Eduardo Fernández-Jover,Pedro Gómez-Vilda,Manuel Graña,Francisco Herrera,Roberto Iglesias,Anna Lekova,Javier de Lope,Ezequiel López-Rubio,Rafael Martínez-Tomás,Miguel A. Molina-Cabello,Antonio S. Montemayor,Paulo Novais,Daniel Palacios-Alonso,Juan José Pantrigo,Bryson R. Payne,Félix de la Paz López,María Angélica Pinninghoff,Mariano Rincón,José Santos,Karl Thurnhofer-Hemsi,Athanasios Tsanas,Ramiro Varela,José Manuel Ferrández +41 more
TL;DR: A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence.
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Restoration of images corrupted by Gaussian and uniform impulsive noise
TL;DR: A principled method to remove both Gaussian or uniform impulsive noise is proposed, based on a Bayesian classification of the input pixels, which is combined with the kernel regression framework.
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Foreground detection in video sequences with probabilistic self-organizing maps.
TL;DR: A new kind of probabilistic background models which is based on Probabilistic self-organising maps is proposed, which is significantly better than its competitors and a strong alternative to classical methods is presented.
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Vehicle type detection by ensembles of convolutional neural networks operating on super resolved images
Miguel A. Molina-Cabello,Rafael Marcos Luque-Baena,Ezequiel López-Rubio,Karl Thurnhofer-Hemsi +3 more
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Assessment of geometric features for individual identification and verification in biometric hand systems
TL;DR: The number of required features have been drastically reduced and good classification rates with about 50 features on average are achieved, with a 100% accuracy using the GA-LDA strategy for the GPDS database and 97% for the CASIA and IITD databases.