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Mostrando ítems 11-20 de 21
VCI-LSTM: Vector choquet integral-based long short-term memory
(IEEE, 2022)
Artículo / Artikulua,
Choquet integral is a widely used aggregation operator on one-dimensional and interval-valued information, since it is able to take into account the possible interaction among data. However, there are many cases where the ...
Fuzzy integrals for edge detection
(Springer, 2023)
Contribución a congreso / Biltzarrerako ekarpena,
In this work, we compare different families of fuzzy integrals
in the context of feature aggregation for edge detection. We analyze the
behaviour of the Sugeno and Choquet integral and some of its generalizations.
In ...
Unsupervised fuzzy measure learning for classifier ensembles from coalitions performance
(IEEE, 2020)
info:eu-repo/semantics/article,
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: ...
d-Choquet integrals: Choquet integrals based on dissimilarities
(Elsevier, 2020)
info:eu-repo/semantics/article,
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 ...
Learning fuzzy measures for aggregation in fuzzy rule-based models
(Springer Verlag, 2018)
info:eu-repo/semantics/conferenceObject,
Fuzzy measures are used to express background knowledge of the information sources. In fuzzy rule-based models, the rule confidence gives an important information about the final classes and their relevance. This work ...
An empirical study on supervised and unsupervised fuzzy measure construction methods in highly imbalanced classification
(IEEE, 2020)
info:eu-repo/semantics/conferenceObject,
The design of an ensemble of classifiers involves the definition of an aggregation mechanism that produces a single response obtained from the information provided by the classifiers. A specific aggregation methodology ...
Generalized decomposition integral
(Elsevier, 2020)
info:eu-repo/semantics/article,
In this paper we propose two different generalizations of the decomposition integral introduced by Even and Lehrer. We modify the product operator merging a given capacity and the decomposition coefficients by some more ...
Enhancing LSTM for sequential image classification by modifying data aggregation
(IEEE, 2021)
Contribución a congreso / Biltzarrerako ekarpena,
Recurrent Neural Networks (RNN) model sequential information and are commonly used for the analysis of time series. The most usual operation to fuse information in RNNs is the sum. In this work, we use a RNN extended type, ...
Neuro-inspired edge feature fusion using Choquet integrals
(Elsevier, 2021)
Artículo / Artikulua,
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 shapes and descriptors. While different ...
Funções de agregação baseadas em integral de Choquet aplicadas em redimensionalização de imagens
(Universidade Passo Fundo, 2019)
info:eu-repo/semantics/article,
The increasing data volume, coupled with the high complexity of these data, has generated the need to develop increasingly efficient knowledge extraction techniques, both in computational cost and precision. Most of the ...