SPINELLI, GIOVANNI VITO
SPINELLI, GIOVANNI VITO
MAT - DIPARTIMENTO DI MATEMATICA
Dottorandi
Enhancing Food Quality Analysis: Deep Neural Network Inversion of NMRD Profiles with Quadrupolar Dips
2024 Davide Evangelista, Liwei Hu, Giovanni V. Spinelli, Fabiana Zama
Enhancing NMR Analysis: Deep Neural Network Inversion of NMRD Profiles with Quadrupolar Dips
2024 Spinelli, GIOVANNI VITO; Zama, Fabiana; Evangelista, Davide; Hu, Liwei
Neural network-based inversion of NMR dispersion profiles for enhanced analysis of food systems
2024 Spinelli, Giovanni Vito; Evangelista, Davide; Hu, Liwei; Zama, Fabiana
Robust Algorithms for the Analysis of Fast-Field-Cycling Nuclear Magnetic Resonance Dispersion Curves
2024 Bortolotti V.; Conte P.; Landi G.; Lo Meo P.; Nagmutdinova A.; Spinelli G.V.; Zama F.
An automatic L1-based regularization method for the analysis of FFC dispersion profiles with quadrupolar peaks
2023 Landi, G.; Spinelli, G. V.; Zama, F.; Martino, D. C.; Conte, P.; Lo Meo, P.; Bortolotti, V.
Inversion method for the analysis of NMRD profiles by means of the software tools ModelFreeFFC and MFMUPenFFC
2022 Giovanni Vito Spinelli, Fabiana Zama, Germana Landi, Pellegrino Conte, Paolo Lo Meo, Leonardo Brizi, Claudia Testa, Anastasiia Nagmutdinova, Villiam Bortolotti
ModelFreeFFC Tool: inversion method and software for the analysis of NMRD profiles
2022 Fabiana Zama, Germana Landi, Giovanni Vito Spinelli, Pellegrino Conte, Paolo Lo Meo, Leonardo Brizi, Claudia Testa, Anastasiia Nagmutdinova, Villiam Bortolotti
Preliminary development of a Magnetic Resonance Fingerprinting framework for fast multiparametric low-field NMR relaxometry
2022 Giovanni Vito Spinelli, Leonardo Brizi, Marco Barbieri, Fabiana Zama, Germana Landi, Villiam Bortolotti, Daniel Remondini, Claudia Testa
| Titolo | Autore(i) | Anno | Periodico | Editore | Tipo | File |
|---|---|---|---|---|---|---|
| Enhancing Food Quality Analysis: Deep Neural Network Inversion of NMRD Profiles with Quadrupolar Dips | Davide Evangelista, Liwei Hu, Giovanni V. Spinelli, Fabiana Zama | 2024-01-01 | - | - | 4.03 Poster | - |
| Enhancing NMR Analysis: Deep Neural Network Inversion of NMRD Profiles with Quadrupolar Dips | Spinelli, GIOVANNI VITO; Zama, Fabiana; Evangelista, Davide; Hu, Liwei | 2024-01-01 | - | - | 4.02 Riassunto (Abstract) | - |
| Neural network-based inversion of NMR dispersion profiles for enhanced analysis of food systems | Spinelli, Giovanni Vito; Evangelista, Davide; Hu, Liwei; Zama, Fabiana | 2024-01-01 | NEURAL COMPUTING & APPLICATIONS | - | 1.01 Articolo in rivista | NMR_net_springer.pdf |
| Robust Algorithms for the Analysis of Fast-Field-Cycling Nuclear Magnetic Resonance Dispersion Curves | Bortolotti V.; Conte P.; Landi G.; Lo Meo P.; Nagmutdinova A.; Spinelli G.V.; Zama F. | 2024-01-01 | COMPUTERS | - | 1.01 Articolo in rivista | computers-13-00129-with-cover.pdf |
| An automatic L1-based regularization method for the analysis of FFC dispersion profiles with quadrupolar peaks | Landi, G.; Spinelli, G. V.; Zama, F.; Martino, D. C.; Conte, P.; Lo Meo, P.; Bortolotti, V. | 2023-01-01 | APPLIED MATHEMATICS AND COMPUTATION | - | 1.01 Articolo in rivista | main_text_AMC.pdf |
| Inversion method for the analysis of NMRD profiles by means of the software tools ModelFreeFFC and MFMUPenFFC | Giovanni Vito Spinelli, Fabiana Zama, Germana Landi, Pellegrino Conte, Paolo Lo Meo, Leonardo Bri...zi, Claudia Testa, Anastasiia Nagmutdinova, Villiam Bortolotti | 2022-01-01 | - | - | 4.03 Poster | - |
| ModelFreeFFC Tool: inversion method and software for the analysis of NMRD profiles | Fabiana Zama, Germana Landi, Giovanni Vito Spinelli, Pellegrino Conte, Paolo Lo Meo, Leonardo Bri...zi, Claudia Testa, Anastasiia Nagmutdinova, Villiam Bortolotti | 2022-01-01 | - | - | 4.03 Poster | - |
| Preliminary development of a Magnetic Resonance Fingerprinting framework for fast multiparametric low-field NMR relaxometry | Giovanni Vito Spinelli, Leonardo Brizi, Marco Barbieri, Fabiana Zama, Germana Landi, Villiam Bort...olotti, Daniel Remondini, Claudia Testa | 2022-01-01 | - | - | 4.03 Poster | - |