Listar por autor "Barba-González, Cristóbal"
Mostrando ítems 1-20 de 32
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A deep learning LSTM-based approach for forecasting annual pollen curves: Olea and Urticaceae pollen types as a case study
Picornell Rodríguez, Antonio; Hurtado-Requena, Sandro José
; Antequera-Gómez, María Luisa; Barba-González, Cristóbal; Ruiz-Mata, Rocío; De Gálvez-Montañez, Enrique; Recio-Criado, María Marta; Trigo-Pérez, María del Mar; Aldana-Montes, José Francisco; Navas-Delgado, Ismael[et al.] (Elsevier, 2023-11-16)
Airborne pollen can trigger allergic rhinitis and other respiratory diseases in the synthesised population, which makes it one of the most relevant biological contaminants. Therefore, implementing accurate forecast systems ... -
About Designing an Observer Pattern-Based Architecture for a Multi-objective Metaheuristic Optimization Framework
Benítez-Hidalgo, Antonio; Nebro-Urbaneja, Antonio Jesús; Durillo, Juan J.; García-Nieto, José Manuel; López-Camacho, Esteban; Barba-González, Cristóbal; Aldana-Montes, José Francisco[et al.] (2018-11-05)
Multi-objective optimization with metaheuristics is an active and popular research field which is supported by the availability of software frameworks providing algorithms, benchmark problems, quality indicators and other ... -
Addressing significant challenges for animal detection in camera trap images: a novel deep learning-based approach.
Mulero-Pázmány, Margarita Cristina; Hurtado-Requena, Sandro José; Barba-González, Cristóbal; Antequera-Gómez, María Luisa; Díaz-Ruiz, Francisco; Real-Giménez, Raimundo; Navas-Delgado, Ismael; Aldana-Montes, José Francisco[et al.] (Springer-Nature, 2025-05-09)
Wildlife biologists increasingly use camera traps for monitoring animal populations. However, manually sifting through the collected images is expensive and time-consuming. Current deep learning studies for camera trap ... -
Algoritmo Evolutivo Multi-Objectivo para la Toma de Decisiones Interactiva en Optimización Dinámica
Barba-González, Cristóbal; García-Nieto, José Manuel; Ruiz-Mora, Ana Belén; Nebro-Urbaneja, Antonio Jesús; Luque-Gallego, Mariano; Aldana-Montes, José Francisco[et al.] (2018-11-09)
Debido al creciente interés en el análisis de datos en streaming en entornos Big Data para la toma de decisiones, cada vez es más común la aparición de problemas de optimización dinámica que involucran dos o más objetivos ... -
Análisis de los datos del acelerómetro para detección de actividades
Hurtado-Requena, Sandro José; Barba-González, Cristóbal; Rybinski, Maciej; Barón-López, Francisco Javier; Warnberg, Julia; Navas-Delgado, Ismael; Aldana-Montes, José Francisco[et al.] (2018-10-03)
La inactividad física es uno de los principales factores de riesgo de mortalidad y su relación con las principales enfermedades crónicas es objeto de intensas investigaciones medicas. Un método objetivo de la evaluación ... -
Aplicación para gestión de datos de flora.
(2023)La recolección de datos es una tarea crucial. Sin embargo, la recopilación manual de los datos puede resultar en errores de escritura que afectan la precisión de los resultados. Para abordar este problema, se han utilizado ... -
Aplicación web de sincronización entre Open Project y Github.
(2023)En todas las empresas de desarrollo software con un número suficiente de empleados es necesaria la organización mediante diferentes metodologías, en concreto, una de las más utilizadas es la metodología SCRUM. Para el ... -
Artificial decision maker driven by PSO: an approach for testing reference point based interactive methods
Ojalehto, Vesa; Nebro-Urbaneja, Antonio Jesús; Miettinen, Kaisa; Aldana-Montes, José Francisco; García-Nieto, José Manuel; Barba-González, Cristóbal[et al.] (2018-09-14)
Over the years, many interactive multiobjective optimization methods based on a reference point have been proposed. With a reference point, the decision maker indicates desirable objective function values to iteratively ... -
Artificial intelligence for automatically detecting animals in camera trap images: a combination of MegaDetector and YOLOv5
Mulero-Pázmány, Margarita Cristina; Hurtado, Sandro; Cardas Ezeiza, Cristian; Antequera-Gómez, María Luisa; Barba-González, Cristóbal; Romero-Pacheco, David; Díaz-Ruiz, Francisco; Navas-Delgado, Ismael; Real-Giménez, Raimundo[et al.] (2023)
Camera traps have gained high popularity for collecting animal images in a cost-effective and non-invasive manner, but manually examining these large volumes of images to extract valuable data is a laborious and costly ... -
Automatic configuration of NSGA-II with jMetal and irace
Nebro-Urbaneja, Antonio Jesús; López-Ibáñez, Manuel; Barba-González, Cristóbal; García-Nieto, José Manuel (ACM, 2019)
jMetal is a Java-based framework for multi-objective optimization with metaheuristics providing, among other features, a wide set of algorithms that are representative of the state-of-the-art. Although it has become a ... -
Big Data Optimization : Algorithmic Framework for Data Analysis Guided by Semantics
Barba-González, Cristóbal (UMA Editorial, 2018-10-30)
Over the past decade the rapid rise of creating data in all domains of knowledge such as traffic, medicine, social network, industry, etc., has highlighted the need for enhancing the process of analyzing large data volumes, ... -
Big Data Optimization: Framework Algorítmico para el análisis de Datos guiado por Semántica
En las últimas décadas el aumento de fuentes de información en diferentes campos de la sociedad desde la salud hasta las redes sociales, ha puesto de manifiesto la necesidad de nuevas técnicas para su análisis, lo que se ... -
Big Data-driven MLOps workflow for annual high-resolution land cover classification models
Burgueño Romero, Antonio Manuel; Barba-González, Cristóbal; Aldana-Montes, José Francisco (Elsevier, 2024-08)
Developing an annual and global high-resolution land cover map is one of the most ambitious tasks in remote sensing, with increasing importance due to the continual rise in validated data and satellite imagery. The success ... -
BIGOWL4DQ: ontology-driven approach for Big Data quality meta-modelling, selection and reasoning
Barba-González, Cristóbal; Caballero, Ismael; Varela-Vaca, Ángel Jesús; Cruz-Lemus, José A.; Gómez López, María Teresa; Navas-Delgado, Ismael[et al.] (Elsevier, 2023-11-27)
Context: Data quality should be at the core of many Artificial Intelligence initiatives from the very first moment in which data is required for a successful analysis. Measurement and evaluation of the level of quality ... -
BIGOWL: Knowledge centered Big Data analytics
Barba-González, Cristóbal; García-Nieto, José Manuel; Roldán-García, María del Mar; Navas-Delgado, Ismael; Nebro-Urbaneja, Antonio Jesús; Aldana-Montes, José Francisco[et al.] (Elsevier, 2018-08-23)
Knowledge extraction and incorporation is currently considered to be beneficial for efficient Big Data analytics. Knowledge can take part in workflow design, constraint definition, parameter selection and configuration, ... -
Dynamic Multi-Objective Optimization With jMetal and Spark: a Case Study
Cordero Benítez, José Andrés; Nebro-Urbaneja, Antonio Jesús; Barba-González, Cristóbal; Durillo, Juan J.; García-Nieto, José Manuel; Navas-Delgado, Ismael; Aldana-Montes, José Francisco[et al.] (2016-09-15)
Technologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines ... -
E-Science workflow: A semantic approach for airborne pollen prediction
Hurtado-Requena, Sandro José; Antequera-Gómez, María Luisa; Barba-González, Cristóbal; Picornell Rodríguez, Antonio; Navas-Delgado, Ismael (Elsevier, 2024-01)
Allergic rhinitis has become a global health problem in recent decades because airborne pollen is a primary trigger of this respiratory disorder. Moreover, pollinosis can exacerbate the symptoms of asthma and favour ... -
Un Framework para Big Data Optimization Basado en jMetal y Spark
Barba-González, Cristóbal; Nebro-Urbaneja, Antonio Jesús; García-Nieto, José Manuel; Cordero Benítez, José Andrés; Durillo, Juan J.; Navas-Delgado, Ismael; Aldana-Montes, José Francisco[et al.] (2016)
Las metaheurísticas multi-objetivo se han convertido en técnicas muy utilizadas para la resolución de problemas complejos de optimización compuestos de varias funciones objetivo en conflicto entre sí. Nos encontramos en ... -
InDM2: interactive dynamic multi-objective decision making using evolutionary algorithms
Nebro-Urbaneja, Antonio Jesús; Ruiz-Mora, Ana Belén; Barba-González, Cristóbal; García-Nieto, José Manuel; Luque-Gallego, Mariano; Aldana-Montes, José Francisco[et al.] (Elsevier, 2018-05-24)
Dynamic optimization problems involving two or more conflicting objectives appear in many real-world scenarios, and more cases are expected to appear in the near future with the increasing interest in the analysis of ... -
Injecting domain knowledge in multi-objective optimization problems: A semantic approach
Barba-González, Cristóbal; Nebro-Urbaneja, Antonio Jesús; García-Nieto, José Manuel; Roldán-García, María del Mar; Navas-Delgado, Ismael; Aldana-Montes, José Francisco[et al.] (Actas de las XXVI Jornadas de Ingeniería del Software y Bases de Datos, 2022-09-05)
In the field of complex problem optimization with me-taheuristics, semantics has been used for modeling different aspects, such as: problem characterization, parameters, decision-maker's preferences, or algorithms. However, ...