• Background modeling by shifted tilings of stacked denoising autoencoders 

      García-González, Jorge; Ortiz-de-lazcano-Lobato, Juan Miguel; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel (2019-06-18)
      The effective processing of visual data without interruption is currently of supreme importance. For that purpose, the analysis system must adapt to events that may affect the data quality and maintain its performance level ...
    • Background modeling for video sequences by stacked denoising autoencoders 

      García-González, Jorge; Ortiz-de-lazcano-Lobato, Juan Miguel; Luque-Baena, Rafael M.; Molina-Cabello, Miguel A.; López-Rubio, Ezequiel (2018-11-05)
      Nowadays, the analysis and extraction of relevant information in visual data flows is of paramount importance. These images sequences can last for hours, which implies that the model must adapt to all kinds of circumstances ...
    • Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras 

      Benito Picazo, Jesús; Domínguez-Merino, Enrique; Palomo, Esteban J.; López-Rubio, Ezequiel; Ortiz-de-lazcano-Lobato, Juan Miguel (IEEE, 2018)
      Automatic video surveillance systems are usually designed to detect anomalous objects being present in a scene or behaving dangerously. In order to perform adequately, they must incorporate models able to achieve accurate ...
    • Sistema de recomendación basado en redes neuronales competitivas 

      Rocha Muñoz, Teresa (2017-04-19)
      En la presente memoria se expone la implementación del algoritmo de un sistema de recomendación basado en el PCACL (Principal Components Analysis Competitive Learning), que es una red neuronal competitiva que realiza un ...