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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 ...
Dissimilarity based choquet integrals
(Springer, 2020)
info:eu-repo/semantics/conferenceObject,
In this paper, in order to generalize the Choquet integral, we replace the difference between inputs in its definition by a restricted dissimilarity function and refer to the obtained function as d-Choquet integral. For ...
Towards fine-grained road maps extraction using sentinel-2 imagery
(Copernicus, 2021)
info:eu-repo/semantics/conferenceObject,
Nowadays, it is highly important to keep road maps up-to-date since a great deal of services rely on them. However, to date, these labours have demanded a great deal of human attention due to their complexity. In the last ...
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 ...
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 ...
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 ...
Additional feature layers from ordered aggregations for deep neural networks
(IEEE, 2020)
info:eu-repo/semantics/conferenceObject,
In the last years we have seen huge advancements in the area of Machine Learning, specially with the use of Deep Neural Networks. One of the most relevant examples is in image classification, where convolutional neural ...
PhantomFields: fast time and spatial multiplexation of acoustic fields for generation of superresolution patterns
(2021)
info:eu-repo/semantics/conferenceObject,
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 ...
Learning super-resolution for Sentinel-2 images with real ground truth data from a reference satellite
(Copernicus, 2020)
info:eu-repo/semantics/conferenceObject,
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 ...