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Verification system based on long-range iris and Graph Siamese Neural Networks
(ACM, 2022)
Contribución a congreso / Biltzarrerako ekarpena,
Biometric systems represent valid solutions in tasks like user authentication and verification, since they are able to analyze physical and behavioural features with high precision. However, especially when physical ...
Multi-temporal data augmentation for high frequency satellite imagery: a case study in Sentinel-1 and Sentinel-2 building and road segmentation
(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 ...
Pushing the limits of Sentinel-2 for building footprint extraction
(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 ...
On the influence of interval normalization in IVOVO fuzzy multi-class classifier
(Springer, 2019)
info:eu-repo/semantics/conferenceObject,
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 ...
Generative adversarial networks for bitcoin data augmentation
(IEEE, 2020)
info:eu-repo/semantics/conferenceObject,
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 ...
Learning channel-wise ordered aggregations in deep neural networks
(Springer, 2021)
info:eu-repo/semantics/conferenceObject,
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 ...
Temporal analysis of distribution shifts in malware classification for digital forensics
(IEEE, 2023)
Contribución a congreso / Biltzarrerako ekarpena,
In recent years, malware diversity and complexity have increased substantially, so the detection and classification of malware families have become one of the key objectives of information security. Machine learning ...
A scalable and flexible Open Source Big Data architecture for small and medium-sized enterprises
(Springer, 2021)
info:eu-repo/semantics/conferenceObject,
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 ...
Gender stereotyping impact in facial expression recognition
(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 ...
An empirical study on supervised and unsupervised fuzzy measure construction methods in highly imbalanced classification
(IEEE, 2020)
info:eu-repo/semantics/conferenceObject,
The design of an ensemble of classifiers involves the definition of an aggregation mechanism that produces a single response obtained from the information provided by the classifiers. A specific aggregation methodology ...