Listar Artículos de revista ISC - ISC aldizkari artikuluak por autor UPNA "Galar Idoate, Mikel"
Mostrando ítems 1-17 de 17
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Addressing the overlapping data problem in classification using the one-vs-one decomposition strategy
Learning good-performing classifiers from data with easily separable classes is not usually a difficult task for most of the algorithms. However, problems affecting classifier performance may arise when samples from different ... -
Attacking bitcoin anonymity: generative adversarial networks for improving bitcoin entity classification
Classification of Bitcoin entities is an important task to help Law Enforcement Agencies reduce anonymity in the Bitcoin blockchain network and to detect classes more tied to illegal activities. However, this task is ... -
Bitcoin and cybersecurity: temporal dissection of blockchain data to unveil changes in entity behavioral patterns
The Bitcoin network not only is vulnerable to cyber-attacks but currently represents the most frequently used cryptocurrency for concealing illicit activities. Typically, Bitcoin activity is monitored by decreasing anonymity ... -
CFM-BD: a distributed rule induction algorithm for building compact fuzzy models in Big Data classification problems
Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions and decisions. However, when it comes to ... -
d-Choquet integrals: Choquet integrals based on dissimilarities
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 ... -
A deep learning approach to an enhanced building footprint and road detection in high-resolution satellite imagery
The detection of building footprints and road networks has many useful applications including the monitoring of urban development, real-time navigation, etc. Taking into account that a great deal of human attention is ... -
Discrete IV dG-Choquet integrals with respect to admissible orders
In this work, we introduce the notion of dG-Choquet integral, which generalizes the discrete Choquet integral replacing, in the first place, the difference between inputs represented by closed subintervals of the unit ... -
An evolutionary underbagging approach to tackle the survival prediction of trauma patients: a case study at the Hospital of Navarre
Survival prediction systems are used among emergency services at hospitals in order to measure their quality objectively. In order to do so, the estimated mortality rate given by a prediction model is compared with the ... -
A framework for radial data comparison and its application to fingerprint analysis
This work tackles the comparison of radial data, and proposes comparison measures that are further applied to fingerprint analysis. First, we study the similarity of scalar and non-scalar radial data, elaborated on previous ... -
FUZZ-EQ: a data equalizer for boosting the discrimination power of fuzzy classifiers
The definition of linguistic terms is a critical part of the construction of any fuzzy classifier. Fuzzy partitioning methods (FPMs) range from simple uniform partitioning to sophisticated optimization algorithms. In this ... -
Fuzzy rule-based classification systems for multi-class problems using binary decomposition strategies: on the influence of n-dimensional overlap functions in the fuzzy reasoning method
Multi-class classification problems appear in a broad variety of real-world problems, e.g., medicine, genomics, bioinformatics, or computer vision. In this context, decomposition strategies are useful to increase the ... -
Multi-class strategies for joint building footprint and road detection in remote sensing
Building footprints and road networks are important inputs for a great deal of services. For instance, building maps are useful for urban planning, whereas road maps are essential for disaster response services. Traditionally, ... -
Network traffic analysis through node behaviour classification: a graph-based approach with temporal dissection and data-level preprocessing
Network traffic analysis is an important cybersecurity task, which helps to classify anomalous, potentially dangerous connections. In many cases, it is critical not only to detect individual malicious connections, but to ... -
A study of OWA operators learned in convolutional neural networks
Ordered Weighted Averaging (OWA) operators have been integrated in Convolutional Neural Networks (CNNs) for image classification through the OWA layer. This layer lets the CNN integrate global information about the image ... -
Super-resolution of Sentinel-2 images using convolutional neural networks and real ground truth data
Earth observation data is becoming more accessible and affordable thanks to the Copernicus programme and its Sentinel missions. Every location worldwide can be freely monitored approximately every 5 days using the ... -
A supervised fuzzy measure learning algorithm for combining classifiers
(Elsevier, 2023) Artículo / ArtikuluaFuzzy measure-based aggregations allow taking interactions among coalitions of the input sources into account. Their main drawback when applying them in real-world problems, such as combining classifier ensembles, is how ... -
Unsupervised fuzzy measure learning for classifier ensembles from coalitions performance
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: ...