no code implementations • SemEval (NAACL) 2022 • Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, Aurora Saibene, Berta Chulvi, Paolo Rosso, Alyssa Lees, Jeffrey Sorensen
The paper describes the SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification (MAMI), which explores the detection of misogynous memes on the web by taking advantage of available texts and images.
no code implementations • 26 Oct 2023 • Matteo Gabardi, Aurora Saibene, Francesca Gasparini, Daniele Rizzo, Fabio Antonio Stella
These signals are typically a combination of neurological activity and noise, originating from various sources, including physiological artifacts like ocular and muscular movements.
no code implementations • 11 Oct 2022 • Aurora Saibene, Silvia Corchs, Mirko Caglioni, Francesca Gasparini
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.
no code implementations • 11 Oct 2022 • Francesca Gasparini, Elisa Cazzaniga, Aurora Saibene
This work focuses on inner speech recognition starting from EEG signals.
no code implementations • 8 Oct 2021 • Aurora Saibene, Francesca Gasparini, Jordi Solé-Casals
The ageing process may lead to cognitive and physical impairments, which may affect elderly everyday life.
1 code implementation • 15 Jun 2021 • Francesca Gasparini, Giulia Rizzi, Aurora Saibene, Elisabetta Fersini
Two further binary labels have been collected from both the experts and the crowdsourcing platform, for memes evaluated as misogynistic, concerning aggressiveness and irony.
no code implementations • 12 Mar 2021 • Aurora Saibene, Francesca Gasparini
Moreover, the proposed GA, based on a novel fitness function here presented, outperforms the benchmark when the two different datasets considered are merged together, showing the effectiveness of our proposal on heterogeneous data.