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Combinations of affinity functions for different community detection algorithms in social networks
(University of Hawaii Press, 2021)
Contribución a congreso / Biltzarrerako ekarpena,
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. One of the most popular problems in social ...
Gated local adaptive binarization using supervised learning
(CEUR Workshop Proceedings (CEUR-WS.org), 2021)
info:eu-repo/semantics/conferenceObject,
Image thresholding is one of the most popular problems in image processing. However, changes inlightning and contrast in an image can cause trouble for the existing algorithms that use a global threshold for all the image. ...
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 ...
OWA operators based on admissible permutations
(IEEE, 2019)
info:eu-repo/semantics/conferenceObject,
In this work we propose a new OWA operator defined on bounded convex posets of a vector-lattice. In order to overcome the non-existence of a total order, which is necessary to obtain a non-decreasing arrangement of the ...
Strengthened ordered directional and other generalizations of monotonicity for aggregation functions
(Springer, 2018)
info:eu-repo/semantics/conferenceObject,
A tendency in the theory of aggregation functions is the generalization of the monotonicity condition. In this work, we examine the latest developments in terms of different generalizations. In particular, we discuss ...
Local properties of strengthened ordered directional and other forms of monotonicity
(Springer, 2019)
info:eu-repo/semantics/conferenceObject,
In this study we discuss some of the recent generalized forms of monotonicity, introduced in the attempt of relaxing the monotonicity condition of aggregation
functions. Specifically, we deal with weak, directional, ordered ...
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, ...