| Scientific machine learning through physics–informed neural networks: Where we are and what’s next S Cuomo, VS Di Cola, F Giampaolo, G Rozza, M Raissi, F Piccialli Journal of Scientific Computing 92 (3), 88, 2022 | 856 | 2022 |
| A survey on deep learning in medicine: Why, how and when? F Piccialli, V Di Somma, F Giampaolo, S Cuomo, G Fortino Information Fusion 66, 111-137, 2021 | 303 | 2021 |
| The role of artificial intelligence in fighting the COVID-19 pandemic F Piccialli, VS Di Cola, F Giampaolo, S Cuomo Information Systems Frontiers 23 (6), 1467-1497, 2021 | 131 | 2021 |
| Decision making in IoT environment through unsupervised learning F Piccialli, G Casolla, S Cuomo, F Giampaolo, VS Di Cola IEEE Intelligent Systems 35 (1), 27-35, 2019 | 68 | 2019 |
| Artificial intelligence and healthcare: Forecasting of medical bookings through multi-source time-series fusion F Piccialli, F Giampaolo, E Prezioso, D Camacho, G Acampora Information Fusion 74, 1-16, 2021 | 62 | 2021 |
| Trust management and evaluation for edge intelligence in the Internet of Things KN Qureshi, A Iftikhar, SN Bhatti, F Piccialli, F Giampaolo, G Jeon Engineering Applications of Artificial Intelligence 94, 103756, 2020 | 56 | 2020 |
| Detection of COVID-19 from CT scan images: A spiking neural network-based approach A Garain, A Basu, F Giampaolo, JD Velasquez, R Sarkar Neural Computing and Applications 33 (19), 12591-12604, 2021 | 54 | 2021 |
| Explainable framework for Glaucoma diagnosis by image processing and convolutional neural network synergy: analysis with doctor evaluation O Deperlioglu, U Kose, D Gupta, A Khanna, F Giampaolo, G Fortino Future Generation Computer Systems 129, 152-169, 2022 | 47 | 2022 |
| Predictive analytics for smart parking: A deep learning approach in forecasting of iot data F Piccialli, F Giampaolo, E Prezioso, D Crisci, S Cuomo ACM Transactions on Internet Technology (TOIT) 21 (3), 1-21, 2021 | 41 | 2021 |
| A machine learning-enhanced biosensor for mercury detection based on an hydrophobin chimera A Pennacchio, F Giampaolo, F Piccialli, S Cuomo, E Notomista, M Spinelli, ... Biosensors and Bioelectronics 196, 113696, 2022 | 31 | 2022 |
| A blockchain-based secure Internet of medical things framework for stress detection P Qi, D Chiaro, F Giampaolo, F Piccialli Information Sciences 628, 377-390, 2023 | 25 | 2023 |
| Designing an efficient parallel spectral clustering algorithm on multi-core processors in Julia Z Huo, G Mei, G Casolla, F Giampaolo Journal of Parallel and Distributed Computing 138, 211-221, 2020 | 25 | 2020 |
| A deep learning approach for path prediction in a location-based IoT system F Piccialli, F Giampaolo, G Casolla, VS Di Cola, K Li Pervasive and Mobile computing 66, 101210, 2020 | 19 | 2020 |
| Physics-informed neural networks approach for 1D and 2D Gray-Scott systems F Giampaolo, M De Rosa, P Qi, S Izzo, S Cuomo Advanced Modeling and Simulation in Engineering Sciences 9 (1), 5, 2022 | 18 | 2022 |
| Predictive medicine for salivary gland tumours identification through deep learning E Prezioso, S Izzo, F Giampaolo, F Piccialli, GDA Orabona, R Cuocolo, ... IEEE Journal of Biomedical and Health Informatics 26 (10), 4869-4879, 2021 | 18 | 2021 |
| FL-Enhance: A federated learning framework for balancing non-IID data with augmented and shared compressed samples D Chiaro, E Prezioso, M Ianni, F Giampaolo Information Fusion 98, 101836, 2023 | 12 | 2023 |
| Neural networks generative models for time series F Gatta, F Giampaolo, E Prezioso, G Mei, S Cuomo, F Piccialli Journal of King Saud University-Computer and Information Sciences 34 (10 …, 2022 | 12 | 2022 |
| Scientific machine learning through physics-informed neural networks: Where we are and what’s next. arXiv 2022 S Cuomo, VS Di Cola, F Giampaolo, G Rozza, M Raissi, F Piccialli arXiv preprint arXiv:2201.05624, 0 | 12 | |
| Path prediction in IoT systems through Markov Chain algorithm F Piccialli, S Cuomo, F Giampaolo, G Casolla, VS Di Cola Future Generation Computer Systems 109, 210-217, 2020 | 11 | 2020 |
| Solving groundwater flow equation using physics-informed neural networks S Cuomo, M De Rosa, F Giampaolo, S Izzo, VS Di Cola Computers & Mathematics with Applications 145, 106-123, 2023 | 9 | 2023 |
Francesco PiccialliProfessor of Computer Science, University of Naples Federico II, Head of MODAL research lab在 unina.it 的电子邮件经过验证
