Listar por autor "Palomo-Ferrer, Esteban José"
Mostrando ítems 1-20 de 29
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A Convolutional Autoencoder and a Neural Gas model based on Bregman Divergences for Hierarchical Color Quantization
Fernández-Rodríguez, Jose David; Palomo-Ferrer, Esteban José
; Benito-Picazo, Jesús; Domínguez-Merino, Enrique; López-Rubio, Ezequiel; Ortega-Zamorano, Francisco[et al.] (Elsevier, 2023)
Color quantization (CQ) is one of the most common and important procedures to be performed on digital images. In this paper, a new approach to hierarchical color quantization is described, presenting a novel neural network ... -
A novel continual learning approach for competitive neural networks
Fernández-Rodríguez, Jose 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 ... -
Are learning styles useful? A new software to analyze correlations with grades and a case study in engineering
Molina-Cabello, Miguel Ángel; Thurnhofer-Hemsi, Karl; Molina Cabello, David; Palomo-Ferrer, Esteban José (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 ... -
Arquitecturas Flexibles, Crecientes y Jerárquicas para Sistemas Neuronales Autoorganizados
Palomo-Ferrer, Esteban José (2016-09-14)
La autoorganización es un proceso de aprendizaje no supervisado mediante el cual se descubren características, relaciones, patrones significativos o prototipos en los datos. Entre los sistemas neuronales autoorganizados ... -
CADICA: A new dataset for coronary artery disease detectionby using invasive coronary angiograph
Jiménez-Partinen, Ariadna; Molina-Cabello, Miguel Ángel; Thurnhofer-Hemsi, Karl; Palomo-Ferrer, Esteban José; Rodríguez Capitán, Jorge; Molina Ramos, Ana Isabel; Jiménez-Navarro, Manuel Francisco[et al.] (Wiley, 2024)
Coronary artery disease (CAD) remains the leading cause of death globally and invasive coronary angiography (ICA) is considered the gold standard of anatomical imaging evaluation when CAD is suspected. However, risk ... -
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-Ferrer, Esteban José (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 ... -
Continuous Chemical Classification in Uncontrolled Environments with Sliding Windows.
González-Monroy, Javier; Palomo-Ferrer, Esteban José; López-Rubio, Ezequiel; Gonzalez-Jimenez, Antonio Javier (Elsevier, 2016-09-03)
Electronic noses are sensing devices able to classify chemical volatiles according to the readings of an array of non-selective gas sensors and some pattern recognition algorithm. Given their high versatility to host ... -
Deep learning for coronary artery disease severity classification
Jiménez-Partinen, Ariadna; Thurnhofer-Hemsi, Karl; Palomo-Ferrer, Esteban José; Molina-Ramos, Ana I. (2023)
Medical imaging evaluations are one of the fields where computed-aid diagnosis could improve the efficiency of diagnosis supporting physician decisions. Cardiovascular Artery Disease (CAD) is diagnosed using the gold ... -
Deep learning-based anomalous object detection system for panoramic cameras managed by a Jetson TX2 board
Benito-Picazo, Jesús; Domínguez-Merino, Enrique; Palomo-Ferrer, Esteban José; Ramos-Jiménez, Gonzalo Pascual; López-Rubio, Ezequiel (IEEE, 2021)
Social conflicts appearing in the media are increas ing public awareness about security issues, resulting in a higher demand of more exhaustive environment monitoring methods. Automatic video surveillance systems are a ... -
Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras
Benito-Picazo, Jesús; Domínguez-Merino, Enrique; Palomo-Ferrer, Esteban José; 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 ... -
Deep learning-based video surveillance system managed by low cost hardware and panoramic cameras
Benito-Picazo, Jesús; Domínguez-Merino, Enrique; Palomo-Ferrer, Esteban José; López-Rubio, Ezequiel (IOS Press, 2020)
The design of automated video surveillance systems often involves the detection of agents which exhibit anomalous or dangerous behavior in the scene under analysis. Models aimed to enhance the video pattern recognition ... -
Detección de estenosis en imágenes coronariográfícas aplicando aprendizaje profundo
(2022-06)Hoy en día las cardiopatías son una de las principales causas de muerte, siendo esencial crear y mantener protocolos de prevención junto con un correcto diagnóstico para aquellos que sufran una enfermedad cardiovascular. ... -
Development of artificial neural network-based object detection algorithms for low-cost hardware devices
(UMA Editorial, 2021-12-01)The human brain is the most complex, powerful and versatile learning machine ever known. Consequently, many scientists of various disciplines are fascinated by its structures and information processing methods. Due to the ... -
Dynamic learning rates for continual unsupervised learning.
Fernández-Rodríguez, Jose David; Palomo-Ferrer, Esteban José; Ortiz-de-Lazcano-Lobato, Juan Miguel; Ramos-Jiménez, Gonzalo Pascual; López-Rubio, Ezequiel (IOS Press, 2023)
The dilemma between stability and plasticity is crucial in machine learning, especially when non-stationary input distributions are considered. This issue can be addressed by continual learning in order to alleviate ... -
Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences
Palomo-Ferrer, Esteban José; 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, ... -
Identificación automática de orgánulos celulares mediante redes neuronales convolucionales de aprendizaje profundo
(2021-09)Las proteínas en nuestro organismo son las encargadas de formar tejidos, transportar sustancias y defender al organismo contra infecciones o agentes patógenos, entre otras funciones. Conociendo la ubicación y el transporte ... -
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 ... -
Motion Detection by Microcontroller for Panning Cameras
Benito-Picazo, Jesús; López-Rubio, Ezequiel; Ortiz-de-Lazcano-Lobato, Juan Miguel; Domínguez-Merino, Enrique; Palomo-Ferrer, Esteban José (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, ... -
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 ... -
Parallel proccessing applied to object detection with a Jetson TX2 embedded system.
Benito-Picazo, Jesús; Fernández-Rodríguez, Jose David; Domínguez-Merino, Enrique; Palomo-Ferrer, Esteban José; López-Rubio, Ezequiel (2023)
Video streams from panoramic cameras represent a powerful tool for automated surveillance systems, but naïve implementations typically require very intensive computational loads for applying deep learning models for automated ...