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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 ...
N-dimensional admissibly ordered interval-valued overlap functions and its influence in interval-valued fuzzy rule-based classification systems
(IEEE, 2021)
info:eu-repo/semantics/article,
Overlap functions are a type of aggregation functions that are not required to be associative, generally used to indicate the overlapping degree between two values. They have been successfully used as a conjunction operator ...
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 ...
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 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 ...
Systematic review of aggregation functions applied to image edge detection
(MDPI, 2023)
Artículo / Artikulua,
Edge detection is a crucial process in numerous stages of computer vision. This field of study has recently gained momentum due to its importance in various applications. The uncertainty, among other characteristics of ...
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 ...
CC-separation measure applied in business group decision making
(SciTePress, 2021)
Contribución a congreso / Biltzarrerako ekarpena,
In business, one of the most important management functions is decision making The Group Modular Choquet Random TOPSIS (GMC-RTOPSIS) is a Multi-Criteria Decision Making (MCDM) method that can work with multiple heterogeneous ...
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 ...
Quantifying external information in social network analysis: an application to comparative mythology
(IEEE, 2023)
Artículo / Artikulua,
Social network analysis is a popular tool to understand the relationships between interacting agents by studying the structural properties of their connections. However, this kind of analysis can miss some of the domain-specific ...