Listar Artículos de revista ISC - ISC aldizkari artikuluak por autor "Takáč, Zdenko"
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d-Choquet integrals: Choquet integrals based on dissimilarities
Bustince Sola, Humberto
; Mesiar, Radko; Fernández Fernández, Francisco Javier ; Galar Idoate, Mikel ; Paternain Dallo, Daniel ; Altalhi, A. H.; Pereira Dimuro, Graçaliz ; Bedregal, Benjamin ; Takáč, Zdenko (Elsevier, 2020)
Artículo / Artikulua 
The paper introduces a new class of functions from [0,1]n to [0,n] called d-Choquet integrals. These functions are a generalization of the 'standard' Choquet integral obtained by replacing the difference in the definition ... -
Discrete IV dG-Choquet integrals with respect to admissible orders
Takáč, Zdenko; Uriz Martín, Mikel Xabier ; Galar Idoate, Mikel ; Paternain Dallo, Daniel ; Bustince Sola, Humberto (Elsevier, 2021)
Artículo / Artikulua
In this work, we introduce the notion of dG-Choquet integral, which generalizes the discrete Choquet integral replacing, in the first place, the difference between inputs represented by closed subintervals of the unit ... -
Extension of restricted equivalence functions and similarity measures for type-2 fuzzy sets
Miguel Turullols, Laura de ; Santiago, Regivan; Wagner, Christian; Garibaldi, Jonathan M.; Takáč, Zdenko; Roldán López de Hierro, Antonio Francisco; Bustince Sola, Humberto (IEEE, 2021)
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In this work we generalize the notion of restricted equivalence function for type-2 fuzzy sets, leading to the notion of extended restricted equivalence functions. We also study how under suitable conditions, these new ... -
A generalization of the Sugeno integral to aggregate interval-valued data: an application to brain computer interface and social network analysis
Fumanal Idocin, Javier ; Takáč, Zdenko; Horanská, Lubomíra; Asmus, Tiago ; Pereira Dimuro, Graçaliz ; Vidaurre, Carmen; Fernández Fernández, Francisco Javier ; Bustince Sola, Humberto (Elsevier, 2022)
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Intervals are a popular way to represent the uncertainty related to data, in which we express the vagueness of each observation as the width of the interval. However, when using intervals for this purpose, we need to use ... -
Generalizing max pooling via (a, b)-grouping functions for convolutional neural networks
Rodríguez Martínez, Iosu ; Asmus, Tiago ; Pereira Dimuro, Graçaliz ; Herrera, Francisco; Takáč, Zdenko; Bustince Sola, Humberto (Elsevier, 2023)
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Due to their high adaptability to varied settings and effective optimization algorithm, Convolutional Neural Networks (CNNs) have set the state-of-the-art on image processing jobs for the previous decade. CNNs work in a ... -
Interval-valued aggregation functions based on moderate deviations applied to motor-imagery-based brain computer interface
Fumanal Idocin, Javier ; Takáč, Zdenko; Fernández Fernández, Francisco Javier ; Sanz Delgado, José Antonio; Goyena Baroja, Harkaitz; Lin, Chin-Teng; Wang, Yu-Kai; Bustince Sola, Humberto (IEEE, 2021)
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In this work we develop moderate deviation functions to measure similarity and dissimilarity among a set of given interval-valued data to construct interval-valued aggregation functions, and we apply these functions in two ... -
Moderate deviation and restricted equivalence functions for measuring similarity between data
Altalhi, A. H.; Forcén Carvalho, Juan Ignacio; Pagola Barrio, Miguel ; Barrenechea Tartas, Edurne ; Bustince Sola, Humberto ; Takáč, Zdenko (Elsevier, 2019)
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In this work we study the relation between moderate deviation functions, restricted dissimilarity functions and restricted equivalence functions. We use moderate deviation functions in order to measure the similarity or ... -
Non-symmetric over-time pooling using pseudo-grouping functions for convolutional neural networks
Ferrero Jaurrieta, Mikel; Paiva, Rui; Cruz, Anderson; Bedregal, Benjamin ; Miguel Turullols, Laura de ; Takáč, Zdenko; López Molina, Carlos ; Bustince Sola, Humberto (Elsevier, 2024)
Artículo / Artikulua
Convolutional Neural Networks (CNNs) are a family of networks that have become state-of-the-art in several fields of artificial intelligence due to their ability to extract spatial features. In the context of natural ...
