6 citations · 9 across the 8 of their papers we have counts for
8 papers
Hierarchical Hypercomplex Network for Multimodal Emotion Recognition
Eleonora Lopez, Aurelio Uncini, Danilo Comminiello
Emotion recognition is relevant in various domains, ranging from healthcare to human-computer interaction. Physiological signals, being beyond voluntary control, offer reliable inf…
Guess What I Think: Streamlined EEG-to-Image Generation with Latent Diffusion Models
Eleonora Lopez, Luigi Sigillo, Federica Colonnese +2
Generating images from brain waves is gaining increasing attention due to its potential to advance brain-computer interface (BCI) systems by understanding how brain signals encode…
TACE: Tumor-Aware Counterfactual Explanations
Eleonora Beatrice Rossi, Eleonora Lopez, Danilo Comminiello
The application of deep learning in medical imaging has significantly advanced diagnostic capabilities, enhancing both accuracy and efficiency. Despite these benefits, the lack of…
PHemoNet: A Multimodal Network for Physiological Signals
Eleonora Lopez, Aurelio Uncini, Danilo Comminiello
Emotion recognition is essential across numerous fields, including medical applications and brain-computer interface (BCI). Emotional responses include behavioral reactions, such a…
Towards Explaining Hypercomplex Neural Networks
Eleonora Lopez, Eleonora Grassucci, Debora Capriotti +1
Hypercomplex neural networks are gaining increasing interest in the deep learning community. The attention directed towards hypercomplex models originates from several aspects, spa…
Hypercomplex Multimodal Emotion Recognition from EEG and Peripheral Physiological Signals
Eleonora Lopez, Eleonora Chiarantano, Eleonora Grassucci +1
Multimodal emotion recognition from physiological signals is receiving an increasing amount of attention due to the impossibility to control them at will unlike behavioral reaction…
Attention-Map Augmentation for Hypercomplex Breast Cancer Classification
Eleonora Lopez, Filippo Betello, Federico Carmignani +2
Breast cancer is the most widespread neoplasm among women and early detection of this disease is critical. Deep learning techniques have become of great interest to improve diagnos…
Multi-View Hypercomplex Learning for Breast Cancer Screening
Eleonora Lopez, Eleonora Grassucci, Danilo Comminiello
Radiologists interpret mammography exams by jointly analyzing all four views, as correlations among them are crucial for accurate diagnosis. Recent methods employ dedicated fusion…