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The evolution of the notion of overlap functions
(Springer, 2021)
info:eu-repo/semantics/bookPart,
In this chapter we make a review of the notion of overlap function. Although originally developed in order to determine up to what extent a given element belongs to two sets, overlap functions have widely developed in the ...
Degree of totalness: how to choose the best admissible permutation for vector fuzzy integration
(Elsevier, 2023)
Artículo / Artikulua,
The use of aggregation operators that require ordering of the data brings a problem when the structures to be aggregated are multi-valued, since there may be several admissible orders. To addressing this problem, the concept ...
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 ...
General grouping functions
(Springer, 2020)
info:eu-repo/semantics/conferenceObject,
Some aggregation functions that are not necessarily associative, namely overlap and grouping functions, have called the attention of many researchers in the recent past. This is probably due to the fact that they are a ...
dCF-integrals: generalizing CF-integrals by means of restricted dissimilarity functions
(IEEE, 2022)
Artículo / Artikulua,
The Choquet integral (CI) is an averaging aggregation function that has been used, e.g., in the fuzzy reasoning method (FRM) of fuzzy rule-based classification systems (FRBCSs) and in multicriteria decision making in order ...
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 ...
On the normalization of interval data
(MDPI, 2020)
info:eu-repo/semantics/article,
The impreciseness of numeric input data can be expressed by intervals. On the other hand, the normalization of numeric data is a usual process in many applications. How do we match the normalization with impreciseness on ...
Generalizing max pooling via (a, b)-grouping functions for convolutional neural networks
(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 generalization of the Sugeno integral to aggregate interval-valued data: an application to brain computer interface and social network analysis
(Elsevier, 2022)
Artículo / Artikulua,
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 ...