Computer vision is a branch of computer science that studies how computers can 'see'. It is a
field that provides significant value for advancements in academia and artificial intelligence …

Purpose In this paper, a new automated procedure based on deep learning methods for
schizophrenia diagnosis is presented. Methods To this aim, electroencephalogram signals …

Spectral fingerprints (SFs) are unique power spectra signatures of human brain regions of
interest (ROIs, Keitel & Gross, 2016). SFs allow for accurate ROI identification and can serve …

Objective. We introduce Sparse exact low resolution electromagnetic tomography
(eLORETA), a novel method for estimating a nonparametric solution to the source …

The relaxed zero-forcing (RZF) beamformer is a quadratically-and-linearly constrained
minimum variance beamformer. The central question addressed in this paper is whether …

We consider the problem of localization of sources of brain electrical activity from
electroencephalographic (EEG) and magnetoencephalographic (MEG) measurements …

Current cognitive architectures are either working at the abstract, symbolic level, or the low,
emergent level related to neural modeling. The best way to understand phenomena is to …

The majority of computer vision and computer graphics programs employ image filtering to
omit and/or excerpt content from the images. It is common practise to use linear translation …