One of the major limitations of brain-computer interfaces (BCI) is the need for a long and tedious calibration period in order for a subject to become proficient with the system. A principal challenge in training a BCI ...

Despite the increasing capabilities of computers to master sophisticated human-like tasks and the recent explosive new wave of Machine Learning-based methods, the interior design field still remains a hard-to-master area, ...

We researched cross-modal statistical learning conducting to experiments: a behavioural one and a neuroimaging one. In the analysis of the later we used neural decoding with temporal generalization.

Eina de gestió de models de Machine Learning en el context del marketing energètic. L'eina explota i medeix el rendimient dels models al núvol. A més, també inclou una aplicació d'escriptori que permet visualitzar les ...

The last decade has been the stage for many groundbreaking Artificial Intelligence technologies, such as revolutionary language models: Generative models capable of synthesizing surprisingly unique data. Such a novelty ...

Diabetic Retinopathy (DR) is the leading cause of human blindness in patients with Type 1 Diabetes Mellitus, primarily due to impaired blood flow in the retina. Although accurately staging this disease can be challenging, ...

Model interpretability is a problem for multivariate data in general and, very specifically, for dimensionality reduction techniques as applied to data visualization. The problem is even bigger for nonlinear dimensionality ...

The master's degree thesis is composed of theoretical and practical parts. The theoretical part describes the basics of predictive data analytics and machine learning algorithms for classification such as Logistic Regression, ...