- RIUMA Principal
- Listar por autor
Listar por autor "López Rubio, Ezequiel"
Mostrando ítems 1-20 de 39
-
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 ... -
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 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 ... -
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 ... -
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 ... -
Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences
Palomo, Esteban J.; Benito Picazo, Jesús; Domínguez-Merino, Enrique; López-Rubio, Ezequiel; Ortega-Zamorano, Francisco (Springer, 2021-09)In this paper, a new color quantization method based on a self-organized artificial neural network called the Growing Hierarchical Bregman Neural Gas (GHBNG) is proposed. This neural network is based on Bregman divergences, ... -
Histopathological image analysis for breast cancer diagnosis by ensembles of convolutional neural networks and genetic algorithms
Molina Cabello, Miguel A.; Rodríguez Rodríguez, José Antonio; Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel (2021-07)One of the most invasive cancer types which affect women is breast cancer. Unfortunately, it exhibits a high mortality rate. Automated histopathological image analysis can help to diagnose the disease. Therefore, computer ... -
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 ...