120 citations · 455 across the 23 of their papers we have counts for
23 papers
A Generalization of the Sugeno integral to aggregate Interval-valued data: an application to Brain Computer Interface and Social Network Analysis
Javier Fumanal-Idocin, Zdenko Takac, Lubomira Horanska +5
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 in…
ARTxAI: Explainable Artificial Intelligence Curates Deep Representation Learning for Artistic Images using Fuzzy Techniques
Javier Fumanal-Idocin, Javier Andreu-Perez, Oscar Cordón +2
Automatic art analysis employs different image processing techniques to classify and categorize works of art. When working with artistic images, we need to take into account furthe…
Abstract homogeneity of interval-valued functions
Ana Shirley Monteiro, Regivan Santiago, Radko Mesiar +4
In this paper we develop the idea of abstract homogeneity in the context of interval-valued (IV) functions endowed with admissible orders and investigate some of its properties.
On Monotonicities of Interval Valued Functions
Ana Shirley Monteiro, Regivan Santiago, Martin Papco +2
In this paper, we develop the notions of weak/directional monotonicity (developed by Sesma-Sara et al. in terms of the \emph{Kulisch-Miranker order}) and the notion of -monoto…
Combinations of Affinity Functions for Different Community Detection Algorithms in Social Networks
Javier Fumanal-Idocin, Oscar Cordón, María Minárová +2
Social network analysis is a popular discipline among the social and behavioural sciences, in which the relationships between different social entities are modelled as a network. O…
The Concept of Semantic Value in Social Network Analysis: an Application to Comparative Mythology
Javier Fumanal-Idocin, Oscar Cordón, Graçaliz Dimuro +2
Human sciences have traditionally relied on human reasoning and intelligence to infer knowledge from a wide range of sources, such as oral and written narrations, reports, and trad…
Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
Tiago da Cruz Asmus, Graçaliz Pereira Dimuro, Benjamín Bedregal +3
Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. Interval-valued overlap functions were defined as an extension to exp…
Neuro-inspired edge feature fusion using Choquet integrals
Cedric Marco-Detchart, Giancarlo Lucca, Carlos Lopez-Molina +3
It is known that the human visual system performs a hierarchical information process in which early vision cues (or primitives) are fused in the visual cortex to compose complex sh…
Fuzzy implication functions constructed from general overlap functions and fuzzy negations
Jocivania Pinheiro, Benjamin Bedregal, Regivan H. N. Santiago +3
Fuzzy implication functions have been widely investigated, both in theoretical and practical fields. The aim of this work is to continue previous works related to fuzzy implication…
Aggregation functions on n-dimensional ordered vectors equipped with an admissible order and an application in multi-criteria group decision-making
Thadeu Milfont, Ivan Mezzomo, Benjamín Bedregal +2
-Dimensional fuzzy sets are a fuzzy set extension where the membership values are n-tuples of real numbers in the unit interval [0,1] increasingly ordered, called n-dimensional…
A fusion method for multi-valued data
Martin Papčo, Iosu Rodríguez-Martínez, Javier Fumanal-Idocin +2
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 result…
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions
Javier Fumanal-Idocin, Yu-Kai Wang, Chin-Teng Lin +3
Brain Computer Interface technologies are popular methods of communication between the human brain and external devices. One of the most popular approaches to BCI is Motor Imagery.…
Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface
Javier Fumanal-Idocin, Zdenko Takáč, Javier Fernández Jose Antonio Sanz +4
In this work we study the use of moderate deviation functions to measure similarity and dissimilarity among a set of given interval-valued data. To do so, we introduce the notion o…
Community detection and Social Network analysis based on the Italian wars of the 15th century
J. Fumanal-Idocin, A. Alonso-Betanzos, O. Cordón +2
In this contribution we study social network modelling by using human interaction as a basis. To do so, we propose a new set of functions, affinities, designed to capture the natur…
Learning ordered pooling weights in image classification
J. I. Forcen, Miguel Pagola, Edurne Barrenechea +1
Spatial pooling is an important step in computer vision systems like Convolutional Neural Networks or the Bag-of-Words method. The spatial pooling purpose is to combine neighbourin…
Adaptive binarization based on fuzzy integrals
Francesco Bardozzo, Borja De La Osa, Lubomira Horanska +6
Adaptive binarization methodologies threshold the intensity of the pixels with respect to adjacent pixels exploiting the integral images. In turn, the integral images are generally…
Co-occurrence of deep convolutional features for image search
J. I. Forcen, Miguel Pagola, Edurne Barrenechea +1
Image search can be tackled using deep features from pre-trained Convolutional Neural Networks (CNN). The feature map from the last convolutional layer of a CNN encodes descriptive…
Admissible orders on fuzzy numbers
Nicolás Zumelzu, Benjamin Bedregal, Edmundo Mansilla +2
From the more than two hundred partial orders for fuzzy numbers proposed in the literature, only a few are total. In this paper, we introduce the notion of admissible order for fuz…
Do we still need fuzzy classifiers for Small Data in the Era of Big Data?
Mikel Elkano, Humberto Bustince, Mikel Galar
The Era of Big Data has forced researchers to explore new distributed solutions for building fuzzy classifiers, which often introduce approximation errors or make strong assumption…
On the usage of the probability integral transform to reduce the complexity of multi-way fuzzy decision trees in Big Data classification problems
Mikel Elkano, Mikel Uriz, Humberto Bustince +1
We present a new distributed fuzzy partitioning method to reduce the complexity of multi-way fuzzy decision trees in Big Data classification problems. The proposed algorithm builds…
CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems
Mikel Elkano, Jose Sanz, Edurne Barrenechea +2
Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions…
Generalized Interval-valued OWA Operators with Interval Weights Derived from Interval-valued Overlap Functions
Benjamin Bedregal, Humberto Bustince, Eduardo Palmeira +2
In this work we extend to the interval-valued setting the notion of an overlap functions and we discuss a method which makes use of interval-valued overlap functions for constructi…
Optical images-based edge detection in Synthetic Aperture Radar images
Gilberto P. Silva Junior, Alejandro C. Frery, Sandra Sandri +3
We address the issue of adapting optical images-based edge detection techniques for use in Polarimetric Synthetic Aperture Radar (PolSAR) imagery. We modify the gravitational edge…