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20232026
most citedGenerative AI Meets Semantic Communication: Evolution and Revolution of Communication Tasks

7 citations · 21 across the 23 of their papers we have counts for

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10 papers · 1 filter

cs.HC2023

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…

cs.AI2023

Dual Quaternion Rotational and Translational Equivariance in 3D Rigid Motion Modelling

Guilherme Vieira, Eleonora Grassucci, Marcos Eduardo Valle +1

Objects' rigid motions in 3D space are described by rotations and translations of a highly-correlated set of points, each with associated coordinates that real-valued netwo…

cs.LG2023

PHYDI: Initializing Parameterized Hypercomplex Neural Networks as Identity Functions

Matteo Mancanelli, Eleonora Grassucci, Aurelio Uncini +1

Neural models based on hypercomplex algebra systems are growing and prolificating for a plethora of applications, ranging from computer vision to natural language processing. Hand…

eess.IV2023

Generalizing Medical Image Representations via Quaternion Wavelet Networks

Luigi Sigillo, Eleonora Grassucci, Aurelio Uncini +1

Neural network generalizability is becoming a broad research field due to the increasing availability of datasets from different sources and for various tasks. This issue is even w…

eess.IV2023

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…

cs.SD2023

Diffusion models for audio semantic communication

Eleonora Grassucci, Christian Marinoni, Andrea Rodriguez +1

Directly sending audio signals from a transmitter to a receiver across a noisy channel may absorb consistent bandwidth and be prone to errors when trying to recover the transmitted…