• 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 ...
    • Blood Cell Classification Using the Hough Transform and Convolutional Neural Networks 

      Molina-Cabello, Miguel Ángel; López-Rubio, Ezequiel; Luque-Baena, Rafael Marcos; Rodríguez-Espinosa, María Jesús; Thurnhofer-Hemsi, Karl (Springer, 2018)
      The detection of red blood cells in blood samples can be crucial for the disease detection in its early stages. The use of image processing techniques can accelerate and improve the effectiveness and efficiency of this ...
    • Color Space Selection for Self-Organizing Map Based Foreground Detection in Video Sequences 

      López-Rubio, Francisco Javier; López-Rubio, Ezequiel; Luque-Baena, Rafael Marcos; Dominguez, Enrique; Palomo, Esteban J. (2014-07-18)
      The selection of the best color space is a fundamental task in detecting foreground objects on scenes. In many situations, especially on dynamic backgrounds, neither grayscale nor RGB color spaces represent the best solution ...
    • Content Based Image Retrieval by Convolutional Neural Networks 

      Hamreras, Safa; Benitez-Rochel, Rafaela; Boucheham, Bachir; Molina-Cabello, Miguel A.; López-Rubio, Ezequiel (2019-06-07)
      In this paper, we present a Convolutional Neural Network (CNN) for feature extraction in Content based Image Retrieval (CBIR). The proposed CNN aims at reducing the semantic gap between low level and high-level features. ...
    • Deep Learning networks with p-norm loss layers for spatial resolution enhancement of 3D medical images 

      Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Roé-Vellvé, Núria; Molina-Cabello, Miguel A. (2019-06-19)
      Nowadays, obtaining high-quality magnetic resonance (MR) images is a complex problem due to several acquisition factors, but is crucial in order to perform good diagnostics. The enhancement of the resolution is a typical ...
    • 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 ...
    • Desarrollo de una aplicación web para la gestión de expedientes de un bufete de abogados 

      Molina Cabello, David (2018-02-22)
      La idea de este proyecto es la creación de una aplicación web que permita al público contactar vía internet con su abogado y seguir online la evolución de su caso hasta su solución final. Para ello, el cliente creará en ...
    • Detección automática de glóbulos rojos mediante la transformada de Hough 

      Rodríguez Espinosa, María Jesús (2018-03-16)
      El presente Trabajo de Fin de Grado consiste en la creación de un programa en MATLAB que consiga la detección y recuento de glóbulos rojos en imágenes de microscopía óptica de sangre. Este estudio tiene como fin obtener, ...
    • Detección de objetos en entornos dinámicos para videovigilancia 

      López Rubio, Francisco Javier (UMA Editorial, 2016)
      La videovigilancia por medios automáticos es un campo de investigación muy activo debido a la necesidad de seguridad y control. En este sentido, existen situaciones que dificultan el correcto funcionamiento de los algoritmos ...
    • Estudio de las propiedades reológicas de sangre con diabetes 

      Lucena Sánchez, Estrella (2018-03-22)
      La diabetes mellitus puede definirse como un trastorno en la actividad normal de las células del organismo cuya característica fundamental es el aumento anormal de la cantidad de glucosa en la sangre. Las personas diabéticas ...
    • Foreground object detection enhancement by adaptive super resolution for video surveillance 

      Molina-Cabello, Miguel A.; Elizondo, David A.; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel (2019-09-16)
      Foreground object detection is a fundamental low level task in current video surveillance systems. It is usually accomplished by keeping a model of the background at each frame pixel. Many background learning algorithms ...
    • Homography estimation with deep convolutional neural networks by random color transformations 

      Molina-Cabello, Miguel A.; Elizondo, David A.; Luque Baena, Rafael Marcos; López-Rubio, Ezequiel (2019-09-13)
      Most classic approaches to homography estimation are based on the filtering of outliers by means of the RANSAC method. New proposals include deep convolutional neural networks. Here a new method for homography estimation ...
    • Image segmentation with the growing neural gas 

      Belani, Sanjay Prem (2017-01-31)
      Over many years algorithms have been proposed as methods for the segmentation of images. Everytime the work has been improved and optimized for better results with much faster algorithms and newer ways to adapt the ...
    • Modelado de temas para el análisis de la similitud entre usuarios en Twitter 

      Puerto San Román, Haritz (2018-03-06)
      La minería de datos en redes sociales está ganando importancia debido a que permite realizar campañas de marketing más precisas. Por ejemplo, Google realiza un análisis de todos nuestros datos: vídeos que vemos, términos ...
    • Modelado de temas para el análisis de la similitud entre usuarios en Twitter 

      Puerto San Román, Haritz (2018-03-22)
      La minería de datos en redes sociales está ganando importancia debido a que permite realizar campañas de marketing más precisas. Por ejemplo, Google realiza un análisis de todos nuestros datos: vídeos que vemos, términos ...
    • Motion Detection by Microcontroller for Panning Cameras 

      Benito-Picazo, Jesús; López-Rubio, Ezequiel; Ortiz-de-Lazcano-Lobato, Juan Miguel; Domínguez, Enrique; Palomo, Esteban J. (2017-07-24)
      Motion detection is the first essential process in the extraction of information regarding moving objects. The approaches based on background difference are the most used with fixed cameras to perform motion detection, ...
    • Neural Controller for PTZ cameras based on nonpanoramic foreground detection 

      Molina-Cabello, Miguel A.; López-Rubio, Ezequiel; Luque-Baena, Rafael Marcos; Domínguez, Enrique; Thurnhofer-Hemsi, Karl (2017-05-29)
      Abstract—In this paper a controller for PTZ cameras based on an unsupervised neural network model is presented. It takes advantage of the foreground mask generated by a nonparametric foreground detection subsystem. Thus, ...
    • A new self-organizing neural gas model based on Bregman divergences 

      Palomo, Esteban J.; Molina-Cabello, Miguel A.; López-Rubio, Ezequiel; Luque-Baena, Rafael Marcos (2018-07-20)
      In this paper, a new self-organizing neural gas model that we call Growing Hierarchical Bregman Neural Gas (GHBNG) has been proposed. Our proposal is based on the Growing Hierarchical Neural Gas (GHNG) in which Bregman ...
    • Optimization of Convolutional Neural Network ensemble classifiers by Genetic Algorithms 

      Molina-Cabello, Miguel A.; Accino, Cristian; López-Rubio, Ezequiel; Thurnhofer-Hemsi, Karl (Springer, 2019)
      Breast cancer exhibits a high mortality rate and it is the most invasive cancer in women. An analysis from histopathological images could predict this disease. In this way, computational image processing might support this ...