| Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events G Franch, D Nerini, M Pendesini, L Coviello, G Jurman, C Furlanello Atmosphere 11 (3), 267, 2020 | 69 | 2020 |
| GBCNet: In-Field Grape Berries Counting for Yield Estimation by Dilated CNNs L Coviello, M Cristoforetti, G Jurman, C Furlanello Applied Sciences 10 (14), 4870, 2020 | 40 | 2020 |
| TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting G Franch, V Maggio, L Coviello, M Pendesini, G Jurman, C Furlanello Scientific Data 7 (1), 234, 2020 | 29 | 2020 |
| MASS-UMAP: Fast and Accurate Analog Ensemble Search in Weather Radar Archives G Franch, G Jurman, L Coviello, M Pendesini, C Furlanello Remote Sensing 11 (24), 2922, 2019 | 12 | 2019 |
| EYE-C: Eye-Contact Robust Detection and Analysis during Unconstrained Child-Therapist Interactions in the Clinical Setting of Autism Spectrum Disorders G Alvari, L Coviello, C Furlanello Brain Sciences 11 (12), 1555, 2021 | 7 | 2021 |
| A temporally and spatially explicit, data-driven estimation of airborne ragweed pollen concentrations across Europe L Makra, I Matyasovszky, G Tusnády, LH Ziska, JJ Hess, LG Nyúl, ... Science of The Total Environment, 167095, 2023 | 3 | 2023 |
| Clustering of Remotely Sensed Time Series using Functional Principal Component Analysis to Monitor Crops L Coviello, FM Martini, L Cesaretti, S Pesaresi, F Solfanelli, A Mancini 2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor …, 2022 | 2 | 2022 |
| In-field grape berries counting for yield estimation using dilated CNNs L Coviello, M Cristoforetti, G Jurman, C Furlanello arXiv preprint arXiv:1909.12083, 2019 | 2 | 2019 |
| TAASRAD19 Radar Scans 2017-2019 G Franch, V Maggio, L Coviello, G Jurman, C Furlanello, M Pendesini | 2 | 2019 |
| TAASRAD19 Radar Scans 2010-2016 G Franch, V Maggio, L Coviello, G Jurman, C Furlanello, P Marta | 2 | 2019 |
| Time Series from Sentinel-2 for Organic Durum Wheat Yield Prediction Using Functional Data Analysis and Deep Learning A Mancini, F Solfanelli, L Coviello, FM Martini, S Mandolesi, R Zanoli Agronomy 14 (1), 109, 2024 | 1 | 2024 |
| TAASRAD19 Radar Sequences 2010-2019 HDF5 G Franch, V Maggio, L Coviello, G Jurman, C Furlanello, P Marta | 1 | 2020 |
| TAASRAD19 Radar Sequences 2010-2019 NetCDF G Franch, V Maggio, L Coviello, G Jurman, C Furlanello, P Marta | 1 | 2020 |
| Forecasting daily total pollen concentrations on a global scale L Makra, L Coviello, A Gobbi, G Jurman, C Furlanello, M Brunato, ... Allergy, 2024 | | 2024 |
| Eye-C: A Deep Learning System for Fine-Grained Eye Contact Analysis to Support ASD Intervention in Real-World Clinical Scenarios G Alvari, C Furlanello, L Coviello, P Venuti INSAR 2023, 2023 | | 2023 |
| Adalitix: a Web Platform for Agricultural Data Analytics L Coviello, M Cristoforetti, C Furlanello | | 2019 |
| Analysis of temporal alignment for Video Classification K Blanc, D Lingrand, A Paladini, L Coviello, D Mitrev, E Söhler, L Guzman, ... 2019 14th IEEE International Conference on Automatic Face & Gesture …, 2019 | | 2019 |
| TAASRAD19 Radar Sequences 2010-2019 G Franch, V Maggio, L Coviello, G Jurman, C Furlanello, M Pendesini | | 2019 |
| Deep Neural Networks and Precision Agriculture for Grape Yield Estimation F Precioso, C Furlanello, L Coviello | | |
