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Listar por autor "López Rubio, Ezequiel"
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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 ... -
Analysis of functional connectome pipelines for the diagnosis of autism spectrum disorders
Maza Quiroga, Rosa María; López Rodríguez, Domingo; Thurnhofer-Hemsi, Karl; Luque-Baena, Rafael M.; Jiménez Valverde, Clara; [et al.] (2022-05)This paper explores the effect of using different pipelines to compute connectomes (matrices representing brain connections) and use them to train machine learning models with the goal of diagnosing Autism Spectrum ... -
Anomalous trajectory detection for automated traffic video surveillance
Fernández Rodríguez, Jose David; García-González, Jorge; Benitez-Rochel, Rafaela; Molina Cabello, Miguel Ángel; López-Rubio, Ezequiel; [et al.] (2022)Vehicle trajectories extracted from traffic video sequences can be helpful for many purposes. In particular, the analysis of detected anomalous trajectories may enhance drivers’ safety. This work proposes a methodology to ... -
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 ... -
Clasificación de imágenes de lesiones cutáneas mediante redes neuronales convolucionales y aprendizaje profundo
García Ciudad, Javier (2020-11-24)El cáncer de piel es el cuarto tipo de cáncer más común en el mundo, el primero en numerosos países y, además, se espera que su incidencia aumente en las próximas décadas. Gran parte de ellos presentan una mortalidad ... -
Clasificación de noticias mediante técnicas de procesamientodel lenguaje natural basadas en aprendizaje profundo
Doblas Martín, Pedro (2021-06)Uno de los sectores más afectados por la evolución tecnológica de los últimos años es el periodístico, debido tanto al auge del periodismo digital como a la personalización de contenidos mediante el estudio de perfiles de ... -
Color Space Selection for Self-Organizing Map Based Foreground Detection in Video Sequences
López-Rubio, Francisco Javier; López-Rubio, Ezequiel; Luque-Baena, Rafael Marcos; Domínguez, 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 jugadores automáticos mediante aprendizaje profundo por refuerzo para videojuegos
Ponce Martínez, Antonio David (2020-01-16)En este proyecto se presenta un modelo de aprendizaje profundo ca- paz de aprender a realizar varias tareas usando el juego de 1993 DOOM como entorno. El agente es entrenado con los píxeles en crudo de la pantalla de ... -
Desarrollo de un clasificador visual de especies de aves mediante redes neuronales convolucionales
Pérez Segarra, Antonio Miguel (2020-01-16)Se ha desarrollado un clasificador visual de especies de aves mediante redes neuronales convolucionales, en lenguaje Python haciendo uso de la libreríaa Keras. Se dispone de un conjunto de datos de 5771 imágenes repartidas ... -
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 ... -
Encoding generative adversarial networks for defense against image classification attacks
Rodríguez Rodríguez, José Antonio; Pérez Bravo, José María; García González, Jorge; Molina-Cabello, Miguel A.; Thurnhofer-Hemsi, Karl; [et al.] (2022)Image classification has undergone a revolution in recent years due to the high performance of new deep learning models. However, severe security issues may impact the performance of these systems. In particular, adversarial ... -
Enhanced transfer learning model by image shifting on a square lattice for skin lesion malignancy assessment
Molina Cabello, Miguel A.; Thurnhofer Hemsi, Karl; Maza Quiroga, Rosa María; Domínguez, Enrique; López-Rubio, Ezequiel; [et al.] (2021)Skin cancer is one of the most prevalent diseases among people. Physicians have a challenge every time they have to determine whether a diseased skin is benign or malign. There exist clinical diagnosis methods (such as ... -
Ensemble ellipse fitting by spatial median consensus
Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel; Blazquez-Parra, Elidia Beatriz; Ladrón de Guevara Muñoz, Carmen; De Cózar Macías, Óscar David (2021)Ellipses are among the most frequently used geometric models in visual pattern recognition and digital image analysis. This work aims to combine the outputs of an ensemble of ellipse fitting methods, so that the deleterious ...