activity
20212023
most citedData Augmentation techniques in time series domain: A survey and taxonomy

340 citations · 516 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2023★ 13 cited

Artificial Intelligence Model for Tumoral Clinical Decision Support Systems

Guillermo Iglesias, Edgar Talavera, Jesús Troya Garcìa +2

Comparative diagnostic in brain tumor evaluation makes possible to use the available information of a medical center to compare similar cases when a new patient is evaluated. By le…

cs.LG2022★ 8 cited

Dynamics of Fourier Modes in Torus Generative Adversarial Networks

Ángel González-Prieto, Alberto Mozo, Edgar Talavera +1

Generative Adversarial Networks (GANs) are powerful Machine Learning models capable of generating fully synthetic samples of a desired phenomenon with a high resolution. Despite th…

cs.LG2022★ 340 cited

Data Augmentation techniques in time series domain: A survey and taxonomy

Guillermo Iglesias, Edgar Talavera, Ángel González-Prieto +2

With the latest advances in Deep Learning-based generative models, it has not taken long to take advantage of their remarkable performance in the area of time series. Deep neural n…

cs.LG2022★ 111 cited

A survey on GANs for computer vision: Recent research, analysis and taxonomy

Guillermo Iglesias, Edgar Talavera, Alberto Díaz-Álvarez

In the last few years, there have been several revolutions in the field of deep learning, mainly headlined by the large impact of Generative Adversarial Networks (GANs). GANs not o…

cs.LG2021★ 12 cited

Improving the quality of generative models through Smirnov transformation

Ángel González-Prieto, Alberto Mozo, Sandra Gómez-Canaval +1

Solving the convergence issues of Generative Adversarial Networks (GANs) is one of the most outstanding problems in generative models. In this work, we propose a novel activation f…

cs.CR2021★ 32 cited

Synthetic flow-based cryptomining attack generation through Generative Adversarial Networks

Alberto Mozo, Ángel González-Prieto, Antonio Pastor +2

Due to the growing rise of cyber attacks in the Internet, flow-based data sets are crucial to increase the performance of the Machine Learning (ML) components that run in network-b…