Listar Artículos de revista DEIM - EIMS Aldizkari artikuluak por autor UPNA "Rodríguez Martínez, Iosu"
Mostrando ítems 1-7 de 7
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Affine construction methodology of aggregation functions
Roldán López de Hierro, Antonio Francisco; Roldán, Concepción; Bustince Sola, Humberto
; Fernández Fernández, Francisco Javier ; Rodríguez Martínez, Iosu ; Fardoun, Habib; Lafuente López, Julio (Elsevier, 2020)
Artículo / Artikulua 
Aggregation functions have attracted much attention in recent times because of its potential use in many areas such us data fusion and decision making. In practice, most of the aggregation functions that scientists use in ... -
From restricted equivalence functions on Ln to similarity measures between fuzzy multisets
Ferrero Jaurrieta, Mikel; Takáč, Zdenko; Rodríguez Martínez, Iosu ; Marco Detchart, Cedric; Bernardini, Ángela; Fernández Fernández, Francisco Javier ; López Molina, Carlos ; Bustince Sola, Humberto (IEEE, 2023)
Artículo / Artikulua
Restricted equivalence functions are well-known functions to compare two numbers in the interval between 0 and 1. Despite the numerous works studying the properties of restricted equivalence functions and their multiple ... -
A fusion method for multi-valued data
Papčo, Martin; Rodríguez Martínez, Iosu ; Fumanal Idocin, Javier ; Altalhi, A. H.; Bustince Sola, Humberto (Elsevier, 2021)
Artículo / Artikulua
In this paper we propose an extension of the notion of deviation-based aggregation function tailored to aggregate multidimensional data. Our objective is both to improve the results obtained by other methods that try to ... -
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)
Artículo / Artikulua
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 ... -
A new family of aggregation functions for intervals
Díaz-Vázquez, Susana; Torres-Manzanera, Emilio; Rico, Noelia; Mesiar, Radko; Rodríguez Martínez, Iosu ; Lafuente López, Julio ; Díaz, Irene; Montes, Susana; Bustince Sola, Humberto (Springer, 2024)
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Aggregation operators are unvaluable tools when different pieces of information have to be taken into account with respect to the same object. They allow to obtain a unique outcome when different evaluations are available ... -
Replacing pooling functions in convolutional neural networks by linear combinations of increasing functions
Rodríguez Martínez, Iosu ; Lafuente López, Julio ; Santiago, Regivan; Pereira Dimuro, Graçaliz ; Herrera, Francisco; Bustince Sola, Humberto (Elsevier, 2022)
Artículo / Artikulua
Traditionally, Convolutional Neural Networks make use of the maximum or arithmetic mean in order to reduce the features extracted by convolutional layers in a downsampling process known as pooling. However, there is no ... -
A study on the suitability of different pooling operators for convolutional neural networks in the prediction of COVID-19 through chest x-ray image analysis
Rodríguez Martínez, Iosu ; Ursúa Medrano, Pablo; Fernández Fernández, Francisco Javier ; Takáč, Zdenko; Bustince Sola, Humberto (Elsevier, 2024)
Artículo / Artikulua
The 2019 coronavirus disease outbreak, caused by the severe acute respiratory syndrome type-2 virus (SARS-CoV-2), was declared a pandemic in March 2020. Since its emergence to the present day, this disease has brought ...
