Elenco Pubblicazioni - Publications (1524)
D. A. Coccomini, N. Messina, C. Gennaro, and F. Falchi. 2022. Combining EfficientNet and Vision Transformers for Video Deepfake Detection. In Image Analysis and Processing – ICIAP 2022: 21st International Conference, Lecce, Italy, May 23–27, 2022
Written by DAVIDE ALESSANDRO COCCOMINI
Deepfakes are the result of digital manipulation to forge realistic yet fake imagery. With the astonishing advances in deep generative models, fake images or videos are nowadays obtained using variational autoencoders (VAEs) or Generative Adversarial…
P. Seghetti, N. Biasi, et al. Low cardiac frequency associated with higher number of extrasistoles in a computational model of Brugada Syndrome. In: 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society
Written by NICCOLÒ BIASI
Brugada Syndrome is a form of idiopathic ventricular fibrillation, to date there is no definitive theory about how ventricular fibrillation is initiated or its substrate. Starting from the clinical observation that cardiac episodes are more…
N. Biasi, P. Seghetti, A. Tognetti. A transmurally heterogeneous model of the ventricular tissue and its application for simulation of Brugada Syndrome. In: 2022 44th Annual International Conference of the IEEE Engineering in Medic
Written by NICCOLÒ BIASI
We present a transmurally heterogeneous phenomenological model of ventricular tissue that is designed to reproduce the most important features of action potential propagation of endocardial, midmyocardial, and epicardial tissue. Our model consists of only 3…
N. Biasi, P. Seghetti, A. Tognetti. Diffuse fibrosis and repolarization disorders explain ventricular arrhythmias in Brugada syndrome: a computational study. Scientific Reports, 2022, 12.1: 1-15.
Written by NICCOLÒ BIASI
In this work, we reported a computational study to quantitatively determine the individual contributions of three candidate arrhythmic factors associated with Brugada Syndrome. In particular, we focused our analysis on the role of structural abnormalities,…
N. Biasi et al. Physics-Based Simulation and Machine Learning for the Practical Implementation of EIT-Based Tactile Sensors. IEEE Sensors Journal, 2022, 22.5: 4186-4196.
Written by NICCOLÒ BIASI
This work reports an innovative framework toward the practical implementation of tactile sensors based on electrical impedance tomography. Particularly, we tested our framework on the development of a piezoresistive insole-shaped sensor prototype. Our approach couples…
