BACCEGA, DANIELE
BACCEGA, DANIELE
INFORMATICA
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Risultati 1 - 4 di 4 (tempo di esecuzione: 0.012 secondi).
An Agent-Based Model to Support Infection Control Strategies at School
2022-01-01 Baccega Daniele, Pernice Simone, Terna Pietro, Castagno Paolo, Moirano Giovenale, Richiardi Lorenzo, Sereno Matteo, Rabellino Sergio, Maule Milena, Beccuti Marco
Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups
2024-01-01 Saglietto, Andrea; Baccega, Daniele; Esposito, Roberto; Anselmino, Matteo; Dusi, Veronica; Fiandrotti, Attilio; De Ferrari, Gaetano Maria
Deep Learning at Scale
2019-01-01 Paolo Viviani, Maurizio Drocco, Daniele Baccega, Iacopo Colonnelli, Marco Aldinucci
Enhancing COVID-19 forecasting precision through the integration of compartmental models, machine learning and variants
2024-01-01 Baccega, Daniele; Castagno, Paolo; Fernández Anta, Antonio; Sereno, Matteo
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| An Agent-Based Model to Support Infection Control Strategies at School | 2022 | Baccega Daniele, Pernice Simone, Terna Pietro, Castagno Paolo, Moirano Giovenale, Richiardi Lorenzo, Sereno Matteo, Rabellino Sergio, Maule Milena, Beccuti Marco | |
| Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups | 2024 | Saglietto, Andrea; Baccega, Daniele; Esposito, Roberto; Anselmino, Matteo; Dusi, Veronica; Fiandrotti, Attilio; De Ferrari, Gaetano Maria | |
| Deep Learning at Scale | 2019 | Paolo Viviani, Maurizio Drocco, Daniele Baccega, Iacopo Colonnelli, Marco Aldinucci | |
| Enhancing COVID-19 forecasting precision through the integration of compartmental models, machine learning and variants | 2024 | Baccega, Daniele; Castagno, Paolo; Fernández Anta, Antonio; Sereno, Matteo |