Computational Intelligence and Image Analysis
Lines of Research
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Daily music listening to reduce work-related stress: a randomized controlled pilot trial
The Effects of COVID-19 Confinement on the Spanish Family: Adaptation or Change?
Ayuso, L; Requena, F; Jimenez-Rodriguez, O; Khamis, N – 2020
Deep learning-based super-resolution of 3D magnetic resonance images by regularly spaced shifting
Thurnhofer-Hemsi, K; Lopez-Rubio, E; Dominguez, E; Luque-Baena, RM; Roe-Vellve, N – 2020
The Forbidden Region Self-Organizing Map Neural Network
Ramos, AD; Lopez-Rubio, E; Palomo, EJ – 2020
Deep learning-based video surveillance system managed by low cost hardware and panoramic cameras
Benito-Picazo, J; Dominguez, E; Palomo, EJ; Lopez-Rubio, E – 2020
Discrete ordered median problem with induced order
Dominguez, E; Marin, A – 2020
Ellipse fitting by spatial averaging of random ensembles
Thurnhofer-Hemsi, K; Lopez-Rubio, E; Blazquez-Parra, EB; Ladron-de-Guevara-Munoz, MC; de-Cozar-Macias, OD – 2020
Exploratory Data Analysis and Foreground Detection with the Growing Hierarchical Neural Forest
Palomo, EJ; Lopez-Rubio, E; Ortega-Zamorano, F; Benitez-Rochel, R – 2020
Foreground detection by ensembles of random polygonal tilings
Molina-Cabello, MA; Elizondo, DA; Luque-Baena, RM; Lopez-Rubio, E – 2020
Machine learning techniques to predict the effectiveness of music therapy: A randomized controlled trial
Ragho, A; Imbriani, M; Imbriani, C; Baiardi, P; Manzoni, S; Gianotti, M; Castelli, M; Vanneschi, L; Vico, F; Manzoni, L – 2020
Multiobjective optimization of deep neural networks with combinations of Lp-norm cost functions for 3D medical image super-resolution
Thurnhofer-Hemsi, K; Lopez-Rubio, E; Roe-Vellve, N; Molina-Cabello, MA – 2020
Opinion Mining, Sentiment Analysis and Emotion Understanding in Advertising: A Bibliometric Analysis
Sanchez-Nunez, P; Cobo, MJ; De las Heras-Pedrosa, C; Pelaez, JI; Herrera-Viedma, E – 2020
A global prediction model for sudden stops of capital flows using decision trees
Salas, MB; Alaminos, D; Fernandez, MA; Lopez-Valverde, F – 2020
Products and services valuation through unsolicited information from social media
Pelaez, JI; Martinez, EA; Vargas, LG – 2020
Aggregation of Convolutional Neural Network Estimations of Homographies by Color Transformations of the Inputs
Molina-Cabello, MA; Elizondo, DA; Luque-Baena, RM; Lopez-Rubio, E – 2020
Reliability of ranking-based decision methods: a new perspective from the alternatives’ supremacy
Karanik, M; Gomez-Ruiz, JA; Pelaez, JI; Bernal, R – 2020
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
Gorriz, JM; Ramirez, J; Ortiz, A; Martinez-Murcia, FJ; Segovia, F; Suckling, J; Leming, M; Zhang, YD; Alvarez-Sanchez, JR; Bologna, G; Bonomini, P; Casado, FE; Charte, D; Charte, F; Contreras, R; Cuesta-Infante, A; Duro, RJ; Fernandez-Caballero, A; Fernandez-Jover, E; Gomez-Vilda, P; Grana, M; Herrera, F; Iglesias, R; Lekova, A; de Lope, J; Lopez-Rubio, E; Martinez-Tomas, R; Molina-Cabello, MA; Montemayor, AS; Novais, P; Palacios-Alonso, D; Pantrigo, JJ; Payne, BR; Lopez, FD; Pinninghoff, MA; Rincon, M; Santos, J; Thurnhofer-Hemsi, K; Tsanas, A; Varela, R; Ferrandez, JM – 2020
Sentiment Analysis and Emotion Understanding during the COVID-19 Pandemic in Spain and Its Impact on Digital Ecosystems
de las Heras-Pedrosa, C; Sanchez-Nunez, P; Pelaez, JI – 2020
Background subtraction by probabilistic modeling of patch features learned by deep autoencoders
Garcia-Gonzalez, J; Ortiz-de-Lazcano-Lobato, JM; Luque-Baena, RM; Lopez-Rubio, E – 2020
The Big Data razor
Lopez-Rubio, E – 2020
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Members
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Researcher in ChargeSerá Investigador de este nivel los Investigadores Responsable que lideren un grupo de investigación del Instituto y sus Co-IR. Esta categoría puede incluir investigadores muy excepcionales en su disciplina.
Ezequiel López Rubio
Email: ezeqlr@lcc.uma.es
ORCID
SCOPUS
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Co-investigator in ChargeSerá Investigador de este nivel los Investigadores Responsable que lideren un grupo de investigación del Instituto y sus Co-IR. Esta categoría puede incluir investigadores muy excepcionales en su disciplina.
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Investigador/a SéniorSerán aquellos que tengan una actividad investigadora de al menos 5 años en la etapa posdoctoral. Estos investigadores estarán adscritos a un Grupo de Investigación liderado por un Investigador Responsable. Las funciones serán las que le tenga asignadas su IR. Pueden liderar una línea de investigación de alguno de los grupos de investigación del Instituto, con financiación competitiva propia, y con potencial para llegar a convertirse responsable de un grupo de investigación.
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Investigadores/as posdoctorales y/o juniorEsta etapa posdoctoral estará restringida a Investigadores del Instituto que tengan el título doctor y no contemplados en los perfiles posteriores. Durante su etapa posdoctoral pueden llegar a liderar proyectos de I+D+i como Investigadores Principales, aunque aún no hayan establecido un nivel significativo de independencia. Además, pueden tener actividades de docencia y/o asistencial más allá de su trabajo de investigación.
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Investigadores/as predoctorales y/o en formación
Los investigadores predoctorales y/o en formación serán aquellos investigadores que realizan investigaciones bajo supervisión en una línea de investigación orientada a la resolución de problemas de salud. Incluye aquellos investigadores que están cursando un doctorado (incluyendo a los contratados Río Hortega)
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