Browsing by Author "Del Ser, Javier"
Now showing items 1-20 of 33
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A prescription of methodological guidelines for comparing bio-inspired optimization algorithms
Latorre De la Fuente, Antonio; Molina Cabrera, Daniel; Osaba Icedo, Eneko; Poyatos Amador, Javier; Del Ser Lorente, Javier ; Herrera Triguero, Francisco (Elsevier, 2021-12)[EN]Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a growing research topic with many competitive bio-inspired algorithms being proposed every year. In such an active area, preparing ... -
Accurate long-term air temperature prediction with Machine Learning models and data reduction techniques
Fister, D.; Pérez Aracil, J.; Peláez Rodríguez, C.; Del Ser Lorente, Javier ; Salcedo Sanz, S. (Elsevier, 2023-03)In this paper, three customised Artificial Intelligence (AI) frameworks, considering Deep Learning, Machine Learning (ML) algorithms and data reduction techniques, are proposed for a problem of long-term summer air temperature ... -
Advances on Time Series Analysis using Elastic Measures of Similarity
Oregui Bravo, Izaskun (2020-07-23)A sequence is a collection of data instances arranged in an structured manner. When thisarrangement is held in the time domain, sequences are instead referred to as time series. As such,each observation in a time series ... -
Algoritmos evolutivos multiobjetivo con codificación Dandelion para el trazado de estrategias de descarga de tráfico oportunista en redes multioperador
Cónsul Godoy, Jone (2017-05-16)Telekomunikazio operadoreen hazkuntzarekin, bai operadore handiak, azpiegitura, antena eta irrati espektro propioak dituztenak, bai operadore birtualak zerbitzuak aurrekoei baliabideak alokatuz eskaintzen dituztenak, gaur ... -
Análisis de datos de mutaciones cancerígenas
Anabel Montecino, Anabel (2017-07)[ES]El informe expuesto a continuación presenta un primer estudio de que mutaciones o conjunto de mutaciones genéticas intervienen en el padecimiento de cáncer. El objetivo es diseñar un conjunto de módulos de SW que ... -
Análisis e implementación de modelos de aprendizaje máquina en tiempo real sensibles a derivas de concepto en plataformas Big Data
Hidalgo García, Jaime (2017-07)[ES]Este proyecto consiste en el diseño, implementación y despliegue de un software que pueda procesar muestras de datos generadas por dispositivos en tiempo real, con objeto de elaborar predicciones basadas en algoritmos ... -
Aprendizaje automático para la anotación de ritmos en parada cardiorrespiratoria
López Manibardo, Eric (2019-12-04)Resumen (castellano) Las paradas cardiorrespiratorias extrahospitalarias (PCREH) se posicionan como una de las principales causas de defunción en los países desarrollados. Ante dicho evento, existen ciertos factores ... -
Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation
Díaz Rodríguez, Natalia; Del Ser Lorente, Javier ; Coeckelbergh, Mark; López de Prado, Marcos; Herrera Viedma, Enrique; Herrera Triguero, Francisco (Elsevier, 2023-11)Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system’s entire life cycle: it should be (1) lawful, (2) ethical, and ... -
Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions
Nan, Yang; Del Ser Lorente, Javier ; Walsh, Simon; Schönlieb, Carola; Roberts, Michael; Selby, Ian; Howard, Kit; Owen, John; Neville, Jon; Guiot, Julien; Ernst, Benoit; Jiménez Pastor, Ana; Alberich Bayarri, Ángel; Menzel, Marion I.; Walsh, Sean; Vos, Wim; Flerin, Nina; Charbonnier, Jean Paul; van Rikxoort, Eva; Chatterjee, Avishek; Woodruff, Henry; Lambin, Philippe; Cerdá Alberich, Leonor; Martí Bonmatí, Luis; Herrera Triguero, Francisco; Yang, Guang (Elsevier, 2022-06)Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different ... -
Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions
Muhammad, Khan; Ullah, Amin; Lloret, Jaime; Del Ser Lorente, Javier ; C. de Albuquerque, Victor Hugo (IEEE, 2021-07)Advances in information and signal processing technologies have a significant impact on autonomous driving (AD), improving driving safety while minimizing the efforts of human drivers with the help of advanced artificial ... -
Deep learning for understanding multilabel imbalanced Chest X-ray datasets
Liz, Helena; Huertas Tato, Javier; Sánchez Montañés, Manuel; Del Ser Lorente, Javier ; Camacho, David (Elsevier, 2023-07)Over the last few years, convolutional neural networks (CNNs) have dominated the field of computer vision thanks to their ability to extract features and their outstanding performance in classification problems, for example ... -
Design and validation of novel methods for long-term road traffic forecasting
Laña Aurrecoechea, Ibai (2018-10-19)Road traffic management is a critical aspect for the design and planning of complex urban transport networks for which vehicle flow forecasting is an essential component. As a testimony of its paramount relevance in transport ... -
Detección de Malware mediante Aprendizaje Profundo
Zufiaurre Soto, Gloria (2019-12-12)[ES] Resumen Las aplicaciones móviles son una fuente de vulnerabilidad para los hackers. Cada vez son más los ataques realizados a través de ellas. Por ello, es muy importante identificar qué aplicaciones son empleadas ... -
Diseño e implementación de hiperheurísticos distribuidos en entornos efímeros complejos
Martínez Quintana, Haritz David (2017-09)... -
ECG-based pulse detection during cardiac arrest using random forest classifier
Elola Artano, Andoni; Aramendi Ecenarro, Elisabete; Irusta Zarandona, Unai; Del Ser Lorente, Javier ; Alonso González, Erik; Daya, Mohamud Ramzan (Springer, 2019)Sudden cardiac arrest is one of the leading causes of death in the industrialized world. Pulse detection is essential for the recognition of the arrest and the recognition of return of spontaneous circulation during therapy, ... -
Edge-enhanced dual discriminator generative adversarial network for fast MRI with parallel imaging using multi-view information
Huang, Jiahao; Ding, Weiping; Lv, Jun; Yang, Jingwen; Dong, Hao; Del Ser Lorente, Javier ; Xia, Jun; Ren, Tiaojuan; Wong, Stephen T.; Yang, Guang (Springer, 2022-10)In clinical medicine, magnetic resonance imaging (MRI) is one of the most important tools for diagnosis, triage, prognosis, and treatment planning. However, MRI suffers from an inherent slow data acquisition process because ... -
Estimación de Matrices Origen-Destino a partir de Datos de Flujo Vehicular
Hurtado Villasante, Borja (2023-05-02)Las matrices origen-destino son una herramienta fundamental dentro del ámbito de la movilidad urbana, ya que describen los patrones de desplazamiento de peatones, transporte público o vehículos a lo largo de un área ... -
From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability
Laña Aurrecoechea, Ibai; Sánchez Medina, Javier J.; Vlahogianni, Eleni I.; Del Ser Lorente, Javier (MDPI, 2021-02-05)Advances in Data Science permeate every field of Transportation Science and Engineering, resulting in developments in the transportation sector that are data-driven. Nowadays, Intelligent Transportation Systems (ITS) could ... -
Fuzz-ClustNet: Coupled fuzzy clustering and deep neural networks for Arrhythmia detection from ECG signals
Kumar, Sanjay; Mallik, Abhishek; Kumar, Akshi; Del Ser Lorente, Javier ; Yang, Guang (Elsevier, 2023-02)Electrocardiogram (ECG) is a widely used technique to diagnose cardiovascular diseases. It is a non-invasive technique that represents the cyclic contraction and relaxation of heart muscles. ECG can be used to detect ... -
Intrinsic Motivation mechanisms for a better sample efficiency in deep reinforcement learning applied to scenarios with sparse rewards
Andrés Fernández, Alain (2023-10-20)Driven by the quest to create intelligent systems that can autonomously learn to make optimal decisions, Reinforcement Learning has emerged as a powerful branch of Machine Learning. Reinforcement Learning agents interact ...