Listar por autor "Molina-Cabello, Miguel Ángel"
Mostrando ítems 21-38 de 38
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Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning
Calderón-Ramírez, Saúl; Murillo-Hernández, Diego; Rojas-Salazar, Kevin; Calvo-Valverde, Luis-Alexander; Yang, Shengxiang; Moemeni, Armaghan; Elizondo Acuña, David Alberto; López-Rubio, Ezequiel
; Molina-Cabello, Miguel Ángel[et al.] (2021-07)
Computer aided diagnosis for mammogram images have seen positive results through the usage of deep learning architectures. However, limited sample sizes for the target datasets might prevent the usage of a deep learning ... -
Infering Air Quality from Traffic Data using Transferable Neural Network Models
Molina-Cabello, Miguel Ángel; Passow, Benjamin N.; Domínguez-Merino, Enrique; Elizondo Acuña, David Alberto; Obszynska, Jolanta (Springer, 2019-06)
This work presents a neural network based model for inferring air quality from traffic measurements. It is important to obtain information on air quality in urban environments in order to meet legislative and policy ... -
Longitudinal study of the learning styles evolution in Engineering degrees
Molina-Cabello, Miguel Ángel; Thurnhofer-Hemsi, Karl; Domínguez, Enrique; López-Rubio, Ezequiel; Palomo-Ferrer, Esteban José (2021)
A learning style describes what are the predominant skills for learning tasks. In the context of university education, knowing the learning styles of the students constitutes a great opportunity to improve both teaching ... -
Mejora de la incertidumbre al usar datos fuera de la distribución (OOD) en un modelo semi-supervisado de aprendizaje profundo
(2022-02)El presente proyecto de investigación tiene como finalidad hacer una comparación entre la distancia de Mahalanobis y la densidad de características (Feature Density) como métodos estimadores de incertidumbre, aplicado a ... -
Neural Controller for PTZ cameras based on nonpanoramic foreground detection
Molina-Cabello, Miguel Ángel; 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-Ferrer, Esteban José; Molina-Cabello, Miguel Ángel; 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 Ángel; 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 ... -
Panoramic Background Modeling for PTZ Cameras with Competitive Learning Neural Networks
Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Domínguez, Enrique; Luque-Baena, Rafael Marcos; Molina-Cabello, Miguel Ángel (2017-05-29)
The construction of a model of the background of a scene still remains as a challenging task in video surveillance systems, in particular for moving cameras. This work presents a novel approach for constructing a panoramic ... -
Peer assessments in Engineering: A pilot project
Thurnhofer-Hemsi, Karl; Molina-Cabello, Miguel Ángel; Palomo-Ferrer, Esteban José; López-Rubio, Ezequiel; Domínguez, Enrique (2021)
The evaluation methods employed in a course are the most important point for the students, above any other learning aspect. For teachers, this task is arduous when the number of students is high. Traditional evaluation ... -
Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments
Molina-Cabello, Miguel Ángel; López-Rubio, Ezequiel; Luque-Baena, Rafael Marcos; Domínguez, Enrique; Palomo-Ferrer, Esteban José
Among current foreground detection algorithms for video sequences, methods based on self-organizing maps are obtaining a greater relevance. In this work we propose a probabilistic self-organising map based model, which ... -
Reconocimiento de enfermedad coronaria en coronariografías mediante Redes Neuronales Convolucionales.
(2023)Las enfermedades cardíacas suponen un serio problema, siendo la principal causa de muerte a nivel mundial. Entre las principales, la más común es la enfermedad de las arterias coronarias (EAC), que ocurre cuando las ... -
Redes neuronales convolucionales para el reconocimiento de enfermedades de la piel
(2022-06)El cáncer de piel es uno de los cánceres más problemáticos a nivel mundial. Dentro de este grupo, se encuentra el melanoma, la forma más mortal de ellos. Además de poder ser detectado de manera temprana mediante una ... -
Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks
García-González, Jorge; Molina-Cabello, Miguel Ángel; Luque-Baena, Rafael Marcos; 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 ... -
Road pollution estimation using static cameras and neural networks
Molina-Cabello, Miguel Ángel; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Deka, Lipika; Thurnhofer-Hemsi, Karl (2018-07-19)
Este artículo presenta una metodología para estimar la contaminación en carreteras mediante el análisis de secuencias de video de tráfico. El objetivo es aprovechar la gran red de cámaras IP existente en el sistema de ... -
Segmentación y detección de objetos en imágenes y vídeo mediante inteligencia computacional
Molina-Cabello, Miguel Ángel (UMA Editorial, 2018-11-09)
La presente tesis trata sobre el procesamiento y análisis de imágenes y video mediante sistemas informáticos. Primeramente se hace una introducción, especificando contexto, objetivos y metodología. Luego se muestran los ... -
Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks
Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel; Roé Vellvé, Nuria; Domínguez-Merino, Enrique; Molina-Cabello, Miguel Ángel (IEEE, 2018)
Enhancing resolution is a permanent goal in magnetic resonance (MR) imaging, in order to keep improving diagnostic capability and registration methods. Super-resolution (SR) techniques are applied at the postprocessing ... -
Vehicle Classification in Traffic Environments Using the Growing Neural Gas
Molina-Cabello, Miguel Ángel; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Ortiz-de-Lazcano-Lobato, Juan Miguel; Domínguez-Merino, Enrique; Muñoz Pérez, José[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 ... -
Vehicle Type Detection by Convolutional Neural Networks
Molina-Cabello, Miguel Ángel; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Thurnhofer-Hemsi, Karl (Springer, 2017)
In this work a new vehicle type detection procedure for traffic surveillance videos is proposed. A Convolutional Neural Network is integrated into a vehicle tracking system in order to accomplish this task. Solutions for ...