BELEN VEGA MARQUEZ

Categoría
Profesor Ayudante Doctor

Contacto

Correo electrónico
Área
Lenguajes y Sistema Informáticos

Investigación

Proyectos y contratos de investigación

Modelos híbridos adaptativos para predecir la producción de energías renovables solar y eólica (P18-RT-2778 - Investigador/a)
IA + IoT para la construcción de Servicios de Hogar Inteligente II (P011-21/E22 - Investigador/a)
Aprendizaje profundo y transferencia de aprendizaje eficientes para salud y movilidad conectada (PID2020-117954RB-C22 - Investigador/a)

Asistencia a congresos

Vega-Márquez, Belén;Riquelme-Santos, José Cristóbal:
Forecasting Greenhouse Temperature Using Machine Learning Models: Optimizing Crop Production in Andalucia. Ponencia en Congreso. 18th International Conference on Soft Computing Models in Industrial and Environmental Applications. Salamanca, Spain. 2023
Jiménez-navarro, Manuel J.;Vega-Márquez, Belén;Luna, José María;Manuel Carranza-García;M. Martínez-Ballesteros:
Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation. Ponencia en Congreso. 14th International Conference on EUropean Transnational Education . Salamanca. 2023
Nepomuceno-Chamorro, Juan Antonio;Vega-Márquez, Belén;Nepomuceno-Chamorro, Isabel De Los Angeles:
Generating Synthetic Fetal Cardiotocography Data with Conditional Generative Adversarial Networks. Ponencia en Congreso. 18th International Conference on Soft Computing Models in Industrial and Environmental Applications. Salamanca, Spain. 2023
Vega-Márquez, Belén;Solís-garcía, Javier ;Nepomuceno-Chamorro, Isabel De Los Angeles;Rubio-Escudero, Cristina:
An Extensive Comparative Between Univariate and Multivariate Deep Learning Models in Day-Ahead Electricity Price Forecasting. Ponencia en Congreso. 16th International Conference on Soft Computing Models in Industrial and Environmental Applications. Bilba. 2021
Vega-Márquez, Belén;Carminati, Andrea;Jurado-Campos, Natividad ;Martín, Andrés;Arce-Jiménez, Lourdes;Rubio-Escudero, Cristina;Nepomuceno-Chamorro, Isabel De Los Angeles:
Convolutional neural networks for olive oil classification. Ponencia en Congreso. International Work-Conference on the Interplay between Natural and Artificial Computation. Cabo de gata (Almería). España.. 2019
Vega-Márquez, Belén;Rubio-Escudero, Cristina;Riquelme-Santos, José Cristóbal;Nepomuceno-Chamorro, Isabel De Los Angeles:
Creation of synthetic data with conditional generative adversarial networks. Ponencia en Congreso. 14th International Conference on Soft Computing Models in Industrial and Environmental Applications. Sevilla. 2019

Artículos publicados

Vega-Márquez, Belén;Nepomuceno-Chamorro, Juan Antonio;Riquelme-Santos, José Cristóbal;Nepomuceno-Chamorro, Isabel De Los Angeles:
Comparing artificial intelligence strategies for early sepsis detection in the ICU: an experimental study. Applied Intelligence. 2023. 10.1007/s10489-023-05124-z.
Martín, Andrés;Rodríguez Hernández, Pablo;Cardador-Dueñas, María José;Vega-Márquez, Belén;Rodríguez-Estévez, Vicente;Arce-Jiménez, Lourdes:
Guidelines to build PLS-DA chemometric classification models using a GC-IMS method: dry-cured ham as a case of study. Talanta Open. 2023. Vol: 7. Núm: 100175. 10.1016/j.talo.2022.100175.
Vega-Márquez, Belén;Rubio-Escudero, Cristina;Nepomuceno-Chamorro, Isabel De Los Angeles:
Generation of Synthetic Data with Conditional Generative Adversarial Networks. Interest Group in Pure and Applied Logics. Logic Journal. 2022. 10.1093/jigpal/jzaa059.
Vega-Márquez, Belén;Rubio-Escudero, Cristina;Nepomuceno-Chamorro, Isabel De Los Angeles;Angel Arcos-Vargas:
Use of Deep Learning Architectures for Day-Ahead Electricity Price Forecasting over Different Time Periods in the Spanish Electricity Market. Applied Sciences. 2021. Vol: 11. Núm: 13. 10.3390/app11136097.
Vega-Márquez, Belén;Nepomuceno-Chamorro, Isabel De Los Angeles;Rubio-Escudero, Cristina;Riquelme-Santos, José Cristóbal:
OCEAn: Ordinal classification with an ensemble approach. Information Sciences. 2021. Vol: 580. Pág. 221-242. 10.1016/j.ins.2021.08.081.
Vega-Márquez, Belén;Nepomuceno-Chamorro, Isabel De Los Angeles;Jurado-Campos, Natividad ;Rubio-Escudero, Cristina:
Deep learning techniques to improve the performance of olive oil classification. Frontiers in Chemistry. 2020. Vol: 7. Núm: 929. 10.3389/fchem.2019.00929.
Nepomuceno-Chamorro, Isabel De Los Angeles;Nepomuceno-Chamorro, Juan Antonio;Galván, José Luis;Vega-Márquez, Belén;Rubio-Escudero, Cristina:
Using prior knowledge in the inference of gene association networks. Applied Intelligence. 2020. Vol: 50. Núm: 11. Pág. 3882-3893. 10.1007/s10489-020-01705-4.