Mostrando ítems 16-20 de 27

    • Feature Selection in Big Image Datasets 

      Figueira-Domínguez, J. Guzmán; Bolón-Canedo, Verónica; Remeseiro, Beatriz (MDPI AG, 2020-08-24)
      [Abstract] In computer vision, current feature extraction techniques generate high dimensional data. Both convolutional neural networks and traditional approaches like keypoint detectors are used as extractors of high-level ...
    • An Agent-Based Model to Simulate the Spread of a Virus Based on Social Behavior and Containment Measures 

      Seijas Carpente, Manuel; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Rodríguez-Arias, Alejandro; Dumitru, Adina (MDPI AG, 2020-08-20)
      [Abstract] COVID-19 has brought a new normality in society. However, to avoid the situation, the virus must be stopped. There are several ways in which the governments of the world have taken action, from small measures ...
    • Adaptive Real-Time Method for Anomaly Detection Using Machine Learning 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (MDPI AG, 2020-08-20)
      [Abstract] Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring ...
    • Usability Heuristics for Domain-Specific Languages (DSLs) 

      Mosqueira-Rey, E.; Alonso Ríos, David (ACM, 2020-03-30)
      [Abstract] The usability of Domain-Specific Languages (DSLs) has been attracting considerable interest from researchers lately. In particular, our literature review found many usability studies that make use of subjective ...
    • Anomaly Detection in IoT: Methods, Techniques and Tools 

      Vigoya, Laura; López-Vizcaíno, Manuel F.; Fernández, Diego; Carneiro, Víctor (MDPI AG, 2019-07-22)
      [Abstract] Nowadays, the Internet of things (IoT) network, as system of interrelated computing devices with the ability to transfer data over a network, is present in many scenarios of everyday life. Understanding how ...