| A comparative analysis of machine/deep learning models for parking space availability prediction FM Awan, Y Saleem, R Minerva, N Crespi Sensors 20 (1), 322, 2020 | 113 | 2020 |
| Improving road traffic forecasting using air pollution and atmospheric data: Experiments based on LSTM recurrent neural networks FM Awan, R Minerva, N Crespi Sensors 20 (13), 3749, 2020 | 48 | 2020 |
| Applying convolutional neural networks with different word representation techniques to recommend bug fixers SFA Zaidi, FM Awan, M Lee, H Woo, CG Lee IEEE Access 8, 213729-213747, 2020 | 39 | 2020 |
| Exploiting digital twins as enablers for synthetic sensing R Minerva, FM Awan, N Crespi IEEE Internet Computing 26 (5), 61-67, 2021 | 30 | 2021 |
| Using noise pollution data for traffic prediction in smart cities: experiments based on LSTM recurrent neural networks FM Awan, R Minerva, N Crespi IEEE Sensors Journal 21 (18), 20722-20729, 2021 | 25 | 2021 |
| Opportunistic digital twin: an edge intelligence enabler for smart city C Savaglio, V Barbuto, FM Awan, R Minerva, N Crespi, G Fortino ACM Transactions on Sensor Networks, 2023 | 4 | 2023 |
| Artificial intelligence and the digital twin: An essential combination R Minerva, N Crespi, R Farahbakhsh, FM Awan The digital twin, 299-336, 2023 | 4 | 2023 |
| Towards synthetic sensing for smart cities: a machine/deep learning-based approach FM Awan Institut Polytechnique de Paris, 2022 | | 2022 |
