Now showing items 1-20 of 332

    • 1920-2015: un siglo de Visión por Computador 

      Medina-Carnicer, R. (Universidad de Córdoba, 2015)
      Dentro de 5 años se cumplirá exactamente un siglo desde la aparición de esta Ciencia a la que aún seguimos refiriéndonos como Visión por Computador. A diferencia de otras Ciencias, con mucha más tradición, conocemos ...
    • A case-study comparison of machine learning approaches for predicting student’s dropout from multiple online educational entities 

      Porras, José Manuel; Lara, Juan A.; Romero, Cristóbal; Ventura Soto, S. (MDPI, 2023)
      Predicting student dropout is a crucial task in online education. Traditionally, each educational entity (institution, university, faculty, department, etc.) creates and uses its own prediction model starting from its own ...
    • A comparative study of many-objective evolutionary algorithms for the discovery of software architectures 

      Ramírez, Aurora; Romero, José Raúl; Ventura Soto, S. (Springer, 2016)
      During the design of complex systems, software architects have to deal with a tangle of abstract artefacts, measures and ideas to discover the most fitting underlying architecture. A common way to structure such complex ...
    • A contrast set mining based approach for cancer subtype analysis 

      Trasierras, Antonio Manuel; Luna, J.M.; Ventura Soto, S. (Elsevier, 2023)
      The task of detecting common and unique characteristics among different cancer subtypes is an important focus of research that aims to improve personalized therapies. Unlike current approaches mainly based on predictive ...
    • A Gene Expression Programming Algorithm for Multi-Label Classification 

      Ávila Jiménez, José Luis; Gibaja, Eva; Zafra Gómez, Amelia; Ventura Soto, S. (Old City Publishing, 2011)
      This paper presents a Gene Expression Programming algorithm for multilabel classification which encodes a discriminant function into each individual to show whether a pattern belongs to a given class or not. The algorithm ...
    • A general framework for boosting feature subset selection algorithms 

      Pérez Rodríguez, Javier; Haro García, Aída de; Romero-del-Castillo, Juan A.; García Pedrajas, Nicolás (Elsevier, 2018)
      Feature selection is one of the most important tasks in many machine learning and data mining problems. Due to the increasing size of the problems, removing useless, erroneous or noisy features is frequently an initial ...
    • A guided data projection technique for classi cation of sovereign ratings: the case of European Union 27 

      Sánchez-Monedero, J.; Campoy-Muñoz, P.; Gutiérrez, P.A.; Hervás-Martínez, César (2017-01-20)
      Sovereign rating has had an increasing importance since the beginning of the nancial crisis. However, credit rating agencies opacity has been criticised by several authors highlighting the suitability of designing more ...
    • A holographic mobile-based application for practicing pronunciation of basic English vocabulary for Spanish speaking children 

      Romero Morales, C.; Cerezo, Rebeca; Calderón, Vicente (Elsevier, 2019)
      This paper describes a holographic mobile-based application designed to help Spanish-speaking children to practice the pronunciation of basic English vocabulary words. The mastery of vocabulary is a fundamental step when ...
    • A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation 

      Durán Rosal, Antonio Manuel; Gutiérrez-Peña, Pedro Antonio; Carmona Poyato, Ángel; Hervás-Martínez, César (Elsevier, 2019)
      This paper proposes new methods based on time series segmentation, including the adaptation of the particle swarm optimisation algorithm (PSO) to this problem, and more advanced PSO versions, such as barebones PSO (BBPSO) ...
    • A memetic dynamic coral reef optimisation algorithm for simultaneous training, design, and optimisation of artificial neural networks 

      Bérchez-Moreno, Francisco; Durán-Rosal, Antonio Manuel; Hervás Martínez, César; Gutiérrez, Pedro A.; Fernández, Juan Carlos (Nature (Springer), 2024)
      Artificial Neural Networks (ANNs) have been used in a multitude of real-world applications given their predictive capabilities, and algorithms based on gradient descent, such as Backpropagation (BP) and variants, are usually ...
    • A method for outlier detection based on cluster analysis and visual expert criteria 

      Lara, Juan A.; Lizcano, David; Rampérez, Víctor; Soriano, Javier (Wiley, 2019)
      Outlier detection is an important problem occurring in a wide range of areas. Outliers are the outcome of fraudulent behaviour, mechanical faults, human error, or simply natural deviations. Many data mining applications ...
    • A Methodology for Buildings Access to Solar Radiation in Sustainable Cities 

      Fernández-Ahumada, Luis Manuel; Ramírez Faz, José; López Luque, Rafael; Márquez García, Álvaro; Varo-Martínez, Marta (MDPI, 2019)
      The growing need to improve the environmental and energy sustainability of buildings involves the use of solar radiation incident on their surfaces. However, in cities, this task is complicated due to the constructive ...
    • A new approach for multi-view gait recognition on unconstrained paths 

      Madrid-Cuevas, F.J.; Carmona Poyato, Ángel; Muñoz-Salinas, Rafael; Medina-Carnicer, R.; López-Fernández, D. (2017)
      Direction changes cause di culties for most of the gait recognition systems, due to appearance changes. We propose a new approach for multi-view gait recognition, which focuses on recognizing people walking on unconstrained ...
    • A new approach for optimal offline time-series segmentation with error bound guarantee 

      Carmona Poyato, Ángel; Fernández García, Nicolás Luis; Madrid-Cuevas, F.J.; Durán Rosal, Antonio Manuel (Elsevier, 2021)
      This paper proposes a new optimal approach, called OSFS, based on feasible space (FS) Liu et al. (2008)[, that minimizes the number of segments of the approximation and guarantees the error bound using the L∞-norm. On the ...
    • A new approach for optimal time-series segmentation 

      Carmona Poyato, Ángel; Fernández García, Nicolás Luis; Madrid-Cuevas, F.J.; Durán Rosal, Antonio Manuel (Elsevier, 2020)
      This paper proposes a new optimal approach, called OSTS, to improve the segmentation of time series. The proposed method is based on A* algorithm and it uses an improved version of the well-known Salotti method for obtaining ...
    • A New Clustering Algorithm Based on Pattern Extraction in Molecular Fingerprints 

      Palacios Bejarano, Bernardo; Cerruela García, Gonzalo; Luque Ruiz, Irene; García-Pedrajas, Nicolás; Gómez-Nieto, Miguel Ángel (2017-12-11)
      In this paper an algorithm for the extraction of patterns in chemical fingerprints is described. As input this algorithm uses a fingerprint representation of the molecule dataset, generating a group of consistent disjoint ...
    • A new thresholding approach for automatic generation of polygonal approximations 

      Fernández García, Nicolás Luis; Moral Martínez, Luis del; Carmona Poyato, Ángel; Medina-Carnicer, R.; Madrid-Cuevas, F.J. (Elsevier, 2016)
      The present paper proposes a new algorithm for automatic generation of polygonal approximations of 2D closed contours based on a new thresholding method. The new proposal computes the signi cance level of the contour points ...
    • A novel backtracking approach for two-axis solar PV tracking plants 

      Fernández-Ahumada, Luis Manuel; Ramírez Faz, José; López Luque, Rafael; Varo-Martínez, Marta; Moreno-García, Isabel; Casares de la Torre, Francisco José (Elsevier, 2020)
      Solar tracking is a technique required to increase energy production in multiple photovoltaic (PV) facilities. In these plants, during low-elevation solar angle hours, shadows appear between the collectors causing a dramatic ...
    • A Novel Low-Cost Sensor Prototype for Monitoring Temperature during Wine Fermentation in Tanks 

      Sainz, Beatriz; Antolín, Jonathan; López-Coronado, Miguel; Castro Lozano, Carlos de (MDPI, 2013)
      This paper presents a multipurpose and low cost sensor for temperature control over the wine fermentation process, in order to steadily communicate data through wireless modules in real time to a viticulturist’s mobile ...
    • A population-based controlled experiment assessing the epidemiological impact of digital contact tracing 

      Rodríguez, Pablo; Graña, Santiago; Alvarez-León, Eva Elisa; Battaglini, Manuela; Darias, Francisco Javier; Hernán, Miguel A.; López, Raquel; Llaneza, Paloma; Martín, Maria Cristina; Ramirez-Rubio, Oriana; Romaní, Adriana; Suárez-Rodríguez, Berta; Sánchez-Monedero, Javier; Arenas, Alex; Lacasa, Lucas (Springer Nature, 2021)
      While Digital contact tracing (DCT) has been argued to be a valuable complement to manual tracing in the containment of COVID-19, no empirical evidence of its effectiveness is available to date. Here, we report the results ...