Listar por autor "Ortiz-de-lazcano-Lobato, Juan Miguel"

Mostrando ítems 1-10 de 10

    • A novel continual learning approach for competitive neural networks 

      Fernández Rodríguez, José David; Maza Quiroga, Rosa María; Palomo Ferrer, Esteban José; Ortiz-de-lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel (2022)
      Continual learning tries to address the stability-plasticity dilemma to avoid catastrophic forgetting when dealing with non-stationary distributions. Prior works focused on supervised or reinforcement learning, but few ...

    • 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 ...

    • Enhanced Perspective Generation by Consensus of NeX neural models 

      Pacheco dos Santos Lima Junior, Marcos Sergio; Fernández Rodríguez, José David; Ortiz-de-lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel; Domínguez-Merino, Enrique (2022-07)
      Neural rendering is a relatively new field of research that aims to produce high quality perspectives of a 3D scene from a reduced set of sample images. This is done with the help of deep artificial neural networks that ...

    • 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, ...

    • Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks 

      García-González, Jorge; Molina Cabello, Miguel Ángel; Luque-Baena, Rafael; Ortiz-de-lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel (ELSEVIER, 2021-12)
      Air quality and reduction of emissions in the transport sector are determinant factors in achieving a sustainable global climate. The monitoring of emissions in traffic routes can help to improve route planning and to ...

    • 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 ...

    • Sistema de reconocimiento óptico de textos manuscritos en español 

      Terrasa Moya, Joaquín Antonio (2020-11-26)
      Recientemente, los avances en computación, en miniaturización de componentes electrónicos, así como la creciente accesibilidad a dispositivos móviles, ha llevado a un aumento exponencial en el número de usuarios de ...

    • 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 ...