The laborious and costly nature of affect annotation is a key detrimenta...
On-screen game footage contains rich contextual information that players...
How can we reliably transfer affect models trained in controlled laborat...
Affective computing strives to unveil the unknown relationship between a...
Affect modeling is viewed, traditionally, as the process of mapping
meas...
In Cultural Heritage, hyperspectral images are commonly used since they
...
Having access to accurate game state information is of utmost importance...
Normalization is a vital process for any machine learning task as it con...
Self-supervised learning (SSL) techniques have been widely used to learn...
Stochastic gradient descent (SGD) is a premium optimization method for
t...
Many of the affect modelling tasks present an asymmetric distribution of...
A key challenge of affective computing research is discovering ways to
r...
An increasing number of emerging applications in data science and engine...
What if emotion could be captured in a general and subject-agnostic fash...
Recent advances in sensing technologies require the design and developme...
In this work we consider the problem of path planning for an autonomous
...
Is it possible to predict the affect of a user just by observing her
beh...
This work regards our preliminary investigation on the problem of path
p...
In this work we propose a method for reducing the dimensionality of tens...
In this paper we propose a tensor-based nonlinear model for high-order d...
In this work, we present tensor-based linear and nonlinear models for
hy...
Detection of moving objects in videos is a crucial step towards successf...
We propose a Gaussian mixture model for background subtraction in infrar...