• Panoramic Background Modeling for PTZ Cameras with Competitive Learning Neural Networks 

      Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Domínguez, Enrique; Luque-Baena, Rafael Marcos; Molina-Cabello, Miguel A. (2017-05-29)
      The construction of a model of the background of a scene still remains as a challenging task in video surveillance systems, in particular for moving cameras. This work presents a novel approach for constructing a panoramic ...
    • Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments 

      Molina-Cabello, Miguel Angel; López-Rubio, Ezequiel; Luque-Baena, Rafael Marcos; Dominguez, Enrique; Palomo, Esteban José
      Among current foreground detection algorithms for video sequences, methods based on self-organizing maps are obtaining a greater relevance. In this work we propose a probabilistic self-organising map based model, which ...
    • Proyecto básico de adecuación de un centro de atención primaria 

      Arrabal Caro, Manuel (2018-12-17)
      La adecuación de un Centro de Atención Primaria es algo fundamental, ya que es necesario que todos los usuarios y profesionales puedan permanecer durante su estancia en las mejores condiciones de confortabilidad y ...
    • Road pollution estimation using static cameras and neural networks 

      Molina-Cabello, Miguel A.; Luque-Baena, Rafael M.; López-Rubio, Ezequiel; Deka, Lipika; Thurnhofer-Hemsi, Karl (2018-07-19)
      Este artículo presenta una metodología para estimar la contaminación en carreteras mediante el análisis de secuencias de video de tráfico. El objetivo es aprovechar la gran red de cámaras IP existente en el sistema de ...
    • Segmentación y detección de objetos en imágenes y vídeo mediante inteligencia computacional 

      Molina Cabello, Miguel Ángel (UMA Editorial, 2018-11-09)
      La presente tesis trata sobre el procesamiento y análisis de imágenes y video mediante sistemas informáticos. Primeramente se hace una introducción, especificando contexto, objetivos y metodología. Luego se muestran los ...
    • Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks 

      Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel; Roé Vellvé, Nuria; Domínguez-Merino, Enrique; Molina Cabello, Miguel Ángel (IEEE, 2018)
      Enhancing resolution is a permanent goal in magnetic resonance (MR) imaging, in order to keep improving diagnostic capability and registration methods. Super-resolution (SR) techniques are applied at the postprocessing ...
    • Vehicle Classification in Traffic Environments Using the Growing Neural Gas 

      Molina-Cabello, Miguel A.; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Ortiz-de-Lazcano-Lobato, Juan Miguel; Domínguez, Enrique; [et al.] (Springer, 2017)
      Traffic monitoring is one of the most popular applications of automated video surveillance. Classification of the vehicles into types is important in order to provide the human traffic controllers with updated information ...
    • Vehicle Type Detection by Convolutional Neural Networks 

      Molina-Cabello, Miguel A.; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Thurnhofer-Hemsi, Karl (Springer, 2017)
      In this work a new vehicle type detection procedure for traffic surveillance videos is proposed. A Convolutional Neural Network is integrated into a vehicle tracking system in order to accomplish this task. Solutions for ...