Listar por autor "Molina-Cabello, Miguel Angel"
Mostrando ítems 1-20 de 37
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Anomalous trajectory detection for automated traffic video surveillance
Fernández Rodríguez, José David; García-González, Jorge; Benitez-Rochel, Rafaela
; Molina-Cabello, Miguel Angel; López-Rubio, Ezequiel; García-González, Jorge[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 ... -
Aplicación de recomendaciones de moda basada en redes de aprendizaje profundo
(2019-12-10)Los sistemas de búsqueda tradicionales de las webs o aplicaciones móviles que realizan las búsquedas mediante un simple texto han evolucionado, dando paso así a los nuevos sistemas basados en la búsqueda por imágenes. En ... -
Are learning styles useful? A new software to analyze correlations with grades and a case study in engineering
Molina-Cabello, Miguel Angel; Thurnhofer Hemsi, Karl Khader; Molina Cabello, David; Palomo-Ferrer, Esteban Jose (Wiley, 2023)
Knowing student learning styles represents an effective way to design the most suitable methodology for our students so that performance can improve with less effort for both students and teachers. However, a methodology ... -
Background modeling for video sequences by stacked denoising autoencoders
García-González, Jorge; Ortiz-de-Lazcano-Lobato, Juan Miguel; Luque-Baena, Rafael Marcos; Molina-Cabello, Miguel Angel; 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 Angel; 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 histopatológicas de cáncer de mama utilizando técnicas de aprendizaje profundo
(2022-09)En la actualidad, el uso de algoritmos clasificadores para el diagnóstico del cáncer es una práctica extendida en la rama de la oncología. Existen una gran cantidad de algoritmos y modelos que ayudan a los profesionales ... -
Comparación de marcos de trabajo de Aprendizaje Profundo para la detección de objetos
Benito Picazo, Jesús; Thurnhofer Hemsi, Karl; Molina-Cabello, Miguel Angel; Domínguez, Enrique (2018-11-08)
Muchas aplicaciones en visión por computador necesitan de sistemas de detección precisos y eficientes. Esta demanda coincide con el auge de la aplicación de técnicas de aprendizaje profundo en casi todos las áreas del ... -
Content Based Image Retrieval by Convolutional Neural Networks
Hamreras, Safa; Benitez-Rochel, Rafaela; Boucheham, Bachir; Molina-Cabello, Miguel Angel; 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 Angel (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 ... -
Desarrollo de una aplicación web para la gestión de expedientes de un bufete de abogados
(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
(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, ... -
Diseño y desarrollo de una aplicación web para alojar algoritmos de reconocimiento de enfermedades dermatológicas
(2022-09)Los modelos de aprendizaje automático son ampliamente utilizados por la comunidad informática desde hace años para realizar tareas de clasificación de imágenes. Una de sus grandes ventajas frente a otros tipos de 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 Angel; Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel[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 Angel; Thurnhofer Hemsi, Karl; Maza Quiroga, Rosa María; Domínguez, Enrique; López-Rubio, Ezequiel; Molina-Cabello, Miguel Angel[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 ... -
Feature density as an uncertainty estimator method in the binary classification mammography images task for a supervised deep learning model
Hernández Vasquez, Marco A; Fuentes Fino, Ricardo Javier; Calderón-Ramírez, Saúl; Domínguez-Merino, Enrique; López-Rubio, Ezequiel; Molina-Cabello, Miguel Angel[et al.] (2022)
Labeled medical datasets may include a limited number of observations for each class, while unlabeled datasets may include observations from patients with pathologies other than those observed in the labeled dataset. This ... -
Foreground object detection enhancement by adaptive super resolution for video surveillance
Molina-Cabello, Miguel Angel; Elizondo Acuña, David Alberto; 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 ... -
Herramienta para el etiquetado de objetos en secuencias de video
(2020-01-20)Uno de los tres pilares sobre los que se sustenta la inteligencia artificial es la disponibilidad de datos públicos etiquetados. En el campo de la visión por ordenador puede llegar a resultar muy complicado, y sobre todo ... -
Histopathological image analysis for breast cancer diagnosis by ensembles of convolutional neural networks and genetic algorithms
Molina-Cabello, Miguel Angel; 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 Angel; Elizondo Acuña, David Alberto; 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 ...