Now showing items 1-3 of 3

    • Capas basadas en operadores OWA para Redes Neuronales Convolucionales 

      Domínguez Catena, Iris (2020)   Trabajo Fin de Máster/Master Amaierako Lana  OpenAccess OpenAccess
      En este trabajo exploramos una nueva forma de ampliar la capacidad de las Redes Neuronales Convolucionales. En concreto, planteamos una nueva t´ecnica para generar informaci´on adicional a partir de la salida de un bloque ...
    • Learning channel-wise ordered aggregations in deep neural networks 

      Domínguez Catena, Iris; Paternain Dallo, Daniel Upna; Galar Idoate, Mikel Upna (Springer, 2021)   Contribución a congreso / Biltzarrerako ekarpena
      One of the most common techniques for approaching image classification problems are Deep Neural Networks. These systems are capable of classifying images with different levels of detail at different levels of detail, with ...
    • Unsupervised fuzzy measure learning for classifier ensembles from coalitions performance 

      Uriz Martín, Mikel Xabier Upna; Paternain Dallo, Daniel Upna; Domínguez Catena, Iris; Bustince Sola, Humberto Upna; Galar Idoate, Mikel Upna (IEEE, 2020)   Artículo / Artikulua  OpenAccess
      In Machine Learning an ensemble refers to the combination of several classifiers with the objective of improving the performance of every one of its counterparts. To design an ensemble two main aspects must be considered: ...