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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 ...
Aggregation functions based on the Choquet integral applied to image resizing
(Atlantis Press, 2019)
info:eu-repo/semantics/conferenceObject,
The rising volume of data and its high complexity has brought the need of developing increasingly efficient knowledge extraction techniques, which demands efficiency both in computational cost and in accuracy. Most of ...
Pre-aggregation functions: construction and an application
(IEEE, 2015)
Artículo / Artikulua,
In this work we introduce the notion of preaggregation
function. Such a function satisfies the same boundary
conditions as an aggregation function, but, instead of requiring
monotonicity, only monotonicity along some ...
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 ...
A proposal for tuning the α parameter in CαC-integrals for application in fuzzy rule-based classification systems
(Springer, 2020)
info:eu-repo/semantics/article,
In this paper, we consider the concept of extended Choquet integral generalized by a copula, called CC-integral. In particular, we adopt a CC-integral that uses a copula defined by a parameter α, which behavior was tested ...
Improving the performance of fuzzy rule-based classification systems based on a nonaveraging generalization of CC-integrals named C-F1F2-integrals
(IEEE, 2019)
info:eu-repo/semantics/article,
A key component of fuzzy rule-based classification systems (FRBCS) is the fuzzy reasoning method (FRM) since it infers the class predicted for new examples. A crucial stage in any FRM is the way in which the information ...
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 ...
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 ...
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, ...
d-XC integrals: on the generalization of the expanded form of the Choquet integral by restricted dissimilarity functions and their applications
(IEEE, 2022)
Artículo / Artikulua,
Restricted dissimilarity functions (RDFs) were introduced to overcome problems resulting from the adoption of the standard difference. Based on those RDFs, Bustince et al. introduced a generalization of the Choquet integral ...