Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Saibene, Aurora"'
Autor:
Gabardi, Matteo, Saibene, Aurora, Gasparini, Francesca, Rizzo, Daniele, Stella, Fabio Antonio
Electroencephalographic (EEG) signals are fundamental to neuroscience research and clinical applications such as brain-computer interfaces and neurological disorder diagnosis. These signals are typically a combination of neurological activity and noi
Externí odkaz:
http://arxiv.org/abs/2310.17335
Autor:
Malaspina, Marika, Barbato, Jessica Amianto, Cremaschi, Marco, Gasparini, Francesca, Grossi, Alessandra, Saibene, Aurora
In the video game industry, great importance is given to the experience that the user has while playing a game. In particular, this experience benefits from the players' perceived sense of being in the game or immersion. The level of user immersion d
Externí odkaz:
http://arxiv.org/abs/2310.16431
This work focuses on inner speech recognition starting from EEG signals. Inner speech recognition is defined as the internalized process in which the person thinks in pure meanings, generally associated with an auditory imagery of own inner "voice".
Externí odkaz:
http://arxiv.org/abs/2210.06472
The Motor Imagery (MI) electroencephalography (EEG) based Brain Computer Interfaces (BCIs) allow the direct communication between humans and machines by exploiting the neural pathways connected to motor imagination. Therefore, these systems open the
Externí odkaz:
http://arxiv.org/abs/2210.06290
Publikováno v:
In Neurocomputing 28 December 2024 610
Publikováno v:
Proceedings of the Italian Workshop on Artificial Intelligence for an Ageing Society 2021 co-located with 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2021) Vol-3108 26-40
The ageing process may lead to cognitive and physical impairments, which may affect elderly everyday life. In recent years, the use of Brain Computer Interfaces (BCIs) based on Electroencephalography (EEG) has revealed to be particularly effective to
Externí odkaz:
http://arxiv.org/abs/2110.03966
Publikováno v:
Data in brief 44 (2022): 108526
In this paper we present a benchmark dataset generated as part of a project for automatic identification of misogyny within online content, which focuses in particular on memes. The benchmark here described is composed of 800 memes collected from the
Externí odkaz:
http://arxiv.org/abs/2106.08409
Autor:
Saibene, Aurora, Gasparini, Francesca
The electroencephalographic (EEG) signals provide highly informative data on brain activities and functions. However, their heterogeneity and high dimensionality may represent an obstacle for their interpretation. The introduction of a priori knowled
Externí odkaz:
http://arxiv.org/abs/2103.07117
Publikováno v:
In Information Processing and Management September 2023 60(5)
Autor:
Gabardi, Matteo1,2,3 (AUTHOR) m.gabardi@campus.unimib.it, Saibene, Aurora1,3 (AUTHOR), Gasparini, Francesca1,3 (AUTHOR), Rizzo, Daniele2 (AUTHOR), Stella, Fabio1,3 (AUTHOR)
Publikováno v:
Intelligenza Artificiale. 2024, Vol. 18 Issue 1, p89-102. 14p.