• Melanoma Recognition by Fusing Convolutional Blocks and Dynamic Routing between Capsules 

      Pérez, Eduardo; Ventura Soto, S. (MDPI, 2021)
      Skin cancer is one of the most common types of cancers in the world, with melanoma being the most lethal form. Automatic melanoma diagnosis from skin images has recently gained attention within the machine learning community, ...
    • Memetic Evolutionary Multi-Objective Neural Network Classifier to Predict Graft Survival in Liver Transplant Patients 

      Cruz-Ramírez, M.; Fernández, Juan Carlos; Fernández-Navarro, F.; Briceño Delgado, Francisco Javier; Mata García, Manuel de la; Hervás-Martínez, César (2017-02-17)
      In liver transplantation, matching donor and recipient is a problem that can be solved using machine learning techniques. In this paper we consider a liver transplant dataset obtained from eleven Spanish hospitals, ...
    • Memetic Pareto Evolutionary Artificial Neural Networks for the determination of growth limits of Listeria Monocytogenes 

      Fernández, J.C.; Gutiérrez, P.A.; Hervás-Martínez, César; Martínez, Francisco J. (2015-10-08)
      The main objective of this work is to automatically design neural network models with sigmoidal basis units for classification tasks, so that classifiers are obtained in the most balanced way possible in terms of CCR ...
    • MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning 

      Belmonte Pérez, Álvaro Andrés; Zafra, Amelia; Gibaja, Eva (Elsevier, 2022)
      MIML library is a Java software tool to develop, test, and compare classification algorithms for multi-instance multi-label (MIML) learning. The library includes 43 algorithms and provides a specific format and facilities ...
    • Minería de datos educativos para la detección de recursos clave 

      Gibaja, Eva; Zafra Gómez, Amelia; Luque Rodríguez, María; Arauzo Azofra, Antonio; Ramírez Quesada, Aurora; Olmo Ortiz, Juan Luis (UCOPress, 2017)
      Este artículo describe un proyecto de innovación educativa centrado en diseñar y desarrollar un nuevo módulo de Moodle que permita obtener modelos predictivos basados en árboles de decisión a partir de los datos de uso ...
    • Mixing body-parts model for 2D human pose estimation in stereo videos 

      López-Quintero, Manuel I.; Marín-Jiménez, M.J.; Muñoz-Salinas, Rafael; Medina-Carnicer, R. (Institution of Engineering and Technology, 2017)
      This study targets 2D articulated human pose estimation (i.e. localisation of body limbs) in stereo videos. Although in recent years depth-based devices (e.g. Microsoft Kinect) have gained popularity, as they perform very ...
    • ML-k’sNN: Label Dependent k Values for Multi-Label k-Nearest Neighbor Rule 

      Cuevas-Muñoz, José Manuel; García Pedrajas, Nicolás (MDPI, 2023)
      Multi-label classification as a data mining task has recently attracted increasing interest from researchers. Many current data mining applications address problems with instances that belong to more than one category. ...
    • Modeling and predicting students’ engagement behaviors using mixture Markov models 

      Maqsood, Rabia; Ceravolo, Paolo; Romero Morales, C.; Ventura Soto, S. (Springer, 2022)
      Students’ engagements reflect their level of involvement in an ongoing learning processwhich can be estimated through their interactions with a computer-based learning or assessment system. A pre-requirement for stimulating ...
    • Modelo de asignación donante-receptor español en transplantes hepáticos 

      Briceño Delgado, Francisco Javier; Mata García, Manuel de la; Cruz Ramírez, Manuel; Hervás-Martínez, César (Consejo Social de la Universidad de Córdoba, 2011)
      El reto que presentan los autores del proyecto se centra en encontrar un modelo español de asignación donante-receptor en trasplantes de hígado que sea válido a un número de pares donantes-receptores. El método que proponen ...
    • Multi-Objective Genetic Programming for Feature Extraction and Data Visualization 

      Cano, Alberto; Ventura Soto, S.; Cios, Krzyztof J. (2017)
      Feature extraction transforms high dimensional data into a new subspace of lower dimensionalitywhile keeping the classification accuracy. Traditional algorithms do not consider the multi-objective nature of this task. ...
    • Multi-source and multimodal data fusion for predicting academic performance in blended learning university courses 

      Chango, Wilson; Cerezo, Rebeca; Romero Morales, C. (Elsevier, 2021)
      In this paper we apply data fusion approaches for predicting the final academic performance of university students using multiple-source, multimodal data from blended learning environments. We collect and preprocess data ...
    • Multi-view gait recognition on curved 

      López-Fernández, D.; Madrid-Cuevas, F.J.; Carmona Poyato, Ángel; Muñoz-Salinas, Rafael; Medina-Carnicer, R. (2017-12-11)
      Appearance changes due to viewing angle changes cause difficulties for most of the gait recognition methods. In this paper, we propose a new approach for multi-view recognition, which allows to recognize people walking on ...
    • Multifractal detrended fluctuation analysis of sheep livestock prices in origin 

      Pavón Domínguez, Pablo; Serrano, Salud; Jiménez-Hornero, Francisco José; Jiménez Hornero, Jorge; Gutiérrez de Ravé Agüera, Eduardo; Ariza Villaverde, Ana Belén (Elsevier, 2013)
      The multifractal detrended fluctuation analysis (MF-DFA) is used to verify whether or not the returns of time series of prices paid to farmers in original markets can be described by the multifractal approach. By way of ...
    • Nonlinear Boosting Projections for Ensemble Construction 

      García-Pedrajas, Nicolás; García-Osorio, César; Fyfe, Colin (Dale Schuurmans, 2007)
      In this paper we propose a novel approach for ensemble construction based on the use of nonlinear projections to achieve both accuracy and diversity of individual classifiers. The proposed approach combines the philosophy ...
    • Object-Based Image Classification of Summer Crops with Machine Learning Methods 

      Gutiérrez, Pedro A.; Hervás-Martínez, César; Six, Johan; Plant, Richard E.; López-Granados, Francisca; Peña, José Manuel (MDPI, 2014)
      The strategic management of agricultural lands involves crop field monitoring each year. Crop discrimination via remote sensing is a complex task, especially if different crops have a similar spectral response and cropping ...
    • On the concept of infinitesimal position vector fields in Galilean spacetimes 

      Caballero, Magdalena; De la Fuente, Daniel; Pelegrín, José A. S.; Rubio, Rafael M. (World Scientific, 2022)
      We introduce two different ways to establish the concept of infinitesimal position vector field between “infinitesimally nearby” observers in a Galilean spacetime as well as show their mathematical equivalence. We also use ...
    • On the geometry of stationary Galilean spacetimes 

      De la Fuente, Daniel; Pelegrín, José A. S.; Rubio, Rafael M. (Springer, 2021)
      In this work we introduce a new family of non-relativistic spacetimes: standard stationary Galilean spacetimes, which constitute the local geometric model of stationary Galilean spacetimes. We also study the geodesic ...
    • Online removal of ocular artefacts from the electroencephalogram 

      Thomlinson, M.; López, J.M.L.; García, M.I.B.; Jervis, B.W. (Institution of Engineering and Technology, 2004)
      A method by which ocular artefacts (OAs) in the electroencephalogram (EEG) may be removed automatically online by electro-oculogram (EOG) subtraction is demonstrated. This is achieved by a combination of recursively ...
    • Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm 

      Jiménez-Fernández, Silvia; Camacho-Gómez, Carlos; Mallol-Poyato, Ricardo; Fernández, Juan Carlos; Ser, Javier del; Portilla-Figueras, Antonio; Salcedo Sanz, S. (MDPI, 2019)
      In this work, a problem of optimal placement of renewable generation and topology design for a Microgrid (MG) is tackled. The problem consists of determining the MG nodes where renewable energy generators must be optimally ...
    • Optimal online time-series segmentation 

      Carmona Poyato, Ángel; Fernández García, Nicolás Luis; Madrid-Cuevas, F.J.; Muñoz-Salinas, Rafael; Romero Ramírez, Francisco J. (Springer, 2024)
      When time series are processed, the difficulty increases with the size of the series. This fact is aggravated when time series are processed online, since their size increases indefinitely. Therefore, reducing their number ...