Listar por autor UPNA "Galar Idoate, Mikel"
Mostrando ítems 21-40 de 49
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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
Elkano Ilintxeta, Mikel
; Galar Idoate, Mikel ; Sanz Delgado, José Antonio ; Bustince Sola, Humberto (Elsevier, 2016)
Artículo / Artikulua 
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 ... -
Gender stereotyping impact in facial expression recognition
Domínguez Catena, Iris ; Paternain Dallo, Daniel ; Galar Idoate, Mikel (Springer, 2023)
Contribución a congreso / Biltzarrerako ekarpena
Facial Expression Recognition (FER) uses images of faces to identify the emotional state of users, allowing for a closer interaction between humans and autonomous systems. Unfortunately, as the images naturally integrate ... -
Generative adversarial networks for bitcoin data augmentation
Zola, Francesco; Bruse, Jan Lukas; Etxeberria Barrio, Xabier; Galar Idoate, Mikel ; Orduna Urrutia, Raúl (IEEE, 2020)
Contribución a congreso / Biltzarrerako ekarpena
In Bitcoin entity classification, results are strongly conditioned by the ground-truth dataset, especially when applying supervised machine learning approaches. However, these ground-truth datasets are frequently affected ... -
INFFC: an iterative class noise filter based on the fusion of classifiers with noise sensitivity control
Sáez, José Antonio; Galar Idoate, Mikel ; Luengo, Julián; Herrera, Francisco (Elsevier, 2015)
Artículo / Artikulua
In classification, noise may deteriorate the system performance and increase the complexity of the models built. In order to mitigate its consequences, several approaches have been proposed in the literature. Among them, ... -
Learning channel-wise ordered aggregations in deep neural networks
Domínguez Catena, Iris ; Paternain Dallo, Daniel ; Galar Idoate, Mikel (Springer, 2021)
Contribución a congreso / Biltzarrerako ekarpena
One of the most common techniques for approaching image classification problems are Deep Neural Networks. These systems are capable of classifying images with different levels of detail at different levels of detail, with ... -
Learning super-resolution for Sentinel-2 images with real ground truth data from a reference satellite
Galar Idoate, Mikel ; Sesma Redín, Rubén ; Ayala Lauroba, Christian; Albizua, Lourdes; Aranda, Carlos (Copernicus, 2020)
Contribución a congreso / Biltzarrerako ekarpena
Copernicus program via its Sentinel missions is making earth observation more accessible and affordable for everybody. Sentinel-2 images provide multi-spectral information every 5 days for each location. However, the maximum ... -
Medical diagnosis of cardiovascular diseases using an interval-valued fuzzy rule-based classification system
Sanz Delgado, José Antonio ; Galar Idoate, Mikel ; Jurío Munárriz, Aránzazu ; Brugos Larumbe, Antonio ; Pagola Barrio, Miguel ; Bustince Sola, Humberto (Elsevier, 2013)
Artículo / Artikulua
Objective: To develop a classifier that tackles the problem of determining the risk of a patient of suffering from a cardiovascular disease within the next ten years. The system has to provide both a diagnosis and an ... -
Mejora de los algoritmos de minería de datos: combinación de clasificadores, preprocesamiento y sus aplicaciones
Uriz Martín, Mikel Xabier (2021)
Tesis doctoral / Doktoretza tesia
El objetivo general de esta tesis es tratar de mejorar los resultados que se obtienen en los problemas de clasificación mejorando las fases que preceden y suceden a la fase de aprendizaje, es decir, a la construcción del ... -
Multi-class strategies for joint building footprint and road detection in remote sensing
Ayala Lauroba, Christian; Aranda, Carlos; Galar Idoate, Mikel (MDPI, 2021)
Artículo / Artikulua
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, ... -
Multi-temporal data augmentation for high frequency satellite imagery: a case study in Sentinel-1 and Sentinel-2 building and road segmentation
Ayala Lauroba, Christian; Aranda Magallón, Coral; Galar Idoate, Mikel (ISPRS, 2022)
Contribución a congreso / Biltzarrerako ekarpena
Semantic segmentation of remote sensing images has many practical applications such as urban planning or disaster assessment. Deep learning-based approaches have shown their usefulness in automatically segmenting large ... -
Network traffic analysis through node behaviour classification: a graph-based approach with temporal dissection and data-level preprocessing
Zola, Francesco; Segurola-Gil, L.; Bruse, Jan Lukas; Galar Idoate, Mikel ; Orduna Urrutia, Raúl (Elsevier, 2022)
Artículo / Artikulua
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 ... -
Novel methodologies for improving fuzzy classifiers: dealing with multi-class and Big Data classification problems
Elkano Ilintxeta, Mikel (2018)
Tesis doctoral / Doktoretza tesia
Los Sistemas de Clasificación Basados en Reglas Difusas (SCBRDs) son métodos de aprendizaje automático que permiten construir modelos predictivos capaces de predecir la clase a la que pertenecen los datos de entrada. La ... -
On the influence of admissible orders in IVOVO
Uriz Martín, Mikel Xabier ; Paternain Dallo, Daniel ; Bustince Sola, Humberto ; Galar Idoate, Mikel (Springer, 2019)
Contribución a congreso / Biltzarrerako ekarpena
It is known that when dealing with interval-valued data, there exist problems associated with the non-existence of a total order. In this work we investigate a reformulation of an interval-valued decomposition strategy for ... -
On the influence of interval normalization in IVOVO fuzzy multi-class classifier
Uriz Martín, Mikel Xabier ; Paternain Dallo, Daniel ; Bustince Sola, Humberto ; Galar Idoate, Mikel (Springer, 2019)
Contribución a congreso / Biltzarrerako ekarpena
IVOVO stands for Inverval-Valued One-Vs-One and is the combination of IVTURS fuzzy classifier and the One-Vs-One strategy. This method is designed to improve the performance of IVTURS in multi-class problems, by dividing ... -
PhantomFields: fast time and spatial multiplexation of acoustic fields for generation of superresolution patterns
Elizondo Martínez, Sonia; Goñi, Jaime; Galar Idoate, Mikel ; Marzo Pérez, Asier (2021)
Contribución a congreso / Biltzarrerako ekarpena
Ultrasonic fields generated by phased arrays can be tailored to obtain a custom pattern of acoustic radiation forces. These force fields can pattern particles as well as be felt by the human hand, enabling applications for ... -
Pushing the limits of Sentinel-2 for building footprint extraction
Ayala Lauroba, Christian; Aranda, Carlos; Galar Idoate, Mikel (IEEE, 2022)
Contribución a congreso / Biltzarrerako ekarpena
Building footprint maps are of high importance nowadays since a wide range of services relies on them to work. However, activities to keep these maps up-to-date are costly and time-consuming due to the great deal of human ... -
A scalable and flexible Open Source Big Data architecture for small and medium-sized enterprises
Iñiguez Jiménez, Luis; Galar Idoate, Mikel (Springer, 2021)
Contribución a congreso / Biltzarrerako ekarpena
The advancements of Big Data, Internet of Things and Artificial Intelligence are causing the industrial revolution known as Industry 4.0. For automated factories, adopting the necessary technologies for its implementation ... -
A study of different families of fusion functions for combining classifiers in the one-vs-one strategy
Uriz Martín, Mikel Xabier ; Paternain Dallo, Daniel ; Jurío Munárriz, Aránzazu ; Bustince Sola, Humberto ; Galar Idoate, Mikel (Springer, 2018)
Contribución a congreso / Biltzarrerako ekarpena
In this work we study the usage of different families of fusion functions for combining classifiers in a multiple classifier system of One-vs-One (OVO) classifiers. OVO is a decomposition strategy used to deal with multi-class ... -
A study of OWA operators learned in convolutional neural networks
Domínguez Catena, Iris ; Paternain Dallo, Daniel ; Galar Idoate, Mikel (MDPI, 2021)
Artículo / Artikulua
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 for Sentinel-2 images
Galar Idoate, Mikel ; Sesma Redín, Rubén ; Ayala Lauroba, Christian; Aranda, Carlos (International Society for Photogrammetry and Remote Sensing, 2019)
Contribución a congreso / Biltzarrerako ekarpena
Obtaining Sentinel-2 imagery of higher spatial resolution than the native bands while ensuring that output imagery preserves the original radiometry has become a key issue since the deployment of Sentinel-2 satellites. ...
