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20242026
most citedGenerative Semantic Communication: Diffusion Models Beyond Bit Recovery

23 citations · 30 across the 9 of their papers we have counts for

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12 papers · 1 filter

cs.LG2024

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…

eess.SP2024

Lightweight Diffusion Models for Resource-Constrained Semantic Communication

Giovanni Pignata, Eleonora Grassucci, Giordano Cicchetti +1

Recently, generative semantic communication models have proliferated as they are revolutionizing semantic communication frameworks, improving their performance, and opening the way…

cs.CV2024

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…

eess.SP2024

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…

cs.CV2024

Ship in Sight: Diffusion Models for Ship-Image Super Resolution

Luigi Sigillo, Riccardo Fosco Gramaccioni, Alessandro Nicolosi +1

In recent years, remarkable advancements have been achieved in the field of image generation, primarily driven by the escalating demand for high-quality outcomes across various ima…

cs.CV2024

Language-Oriented Semantic Latent Representation for Image Transmission

Giordano Cicchetti, Eleonora Grassucci, Jihong Park +3

In the new paradigm of semantic communication (SC), the focus is on delivering meanings behind bits by extracting semantic information from raw data. Recent advances in data-to-tex…