| Data-driven estimation of actual evapotranspiration to support irrigation management: Testing two novel methods based on an unoccupied aerial vehicle and an artificial neural … O Rozenstein, L Fine, N Malachy, A Richard, C Pradalier, J Tanny Agricultural Water Management 283, 108317, 2023 | 15 | 2023 |
| Introducing state-of-the-art deep learning technique for gap-filling of eddy covariance crop evapotranspiration data L Fine, A Richard, J Tanny, C Pradalier, R Rosa, O Rozenstein Water 14 (5), 763, 2022 | 12 | 2022 |
| Filling gaps in micro-meteorological data A Richard, L Fine, O Rozenstein, J Tanny, M Geist, C Pradalier Machine Learning and Knowledge Discovery in Databases. Applied Data Science …, 2021 | 8 | 2021 |
| Semantic nearest neighbor fields monocular edge visual-odometry X Wu, A Benbihi, A Richard, C Pradalier arXiv preprint arXiv:1904.00738, 2019 | 8 | 2019 |
| Omnilrs: A photorealistic simulator for lunar robotics A Richard, J Kamohara, K Uno, S Santra, D van der Meer, ... 2024 IEEE International Conference on Robotics and Automation (ICRA), 16901 …, 2024 | 7 | 2024 |
| REALMS: Resilient exploration and lunar mapping system D Van Der Meer, L Chovet, A Bera, A Richard, PJ Sánchez Cuevas, ... Frontiers in Robotics and AI 10, 1127496, 2023 | 7 | 2023 |
| Deep learning for the detection of semantic features in tree X-ray CT scans S Khazem, A Richard, J Fix, C Pradalier Artificial Intelligence in Agriculture 7, 13-26, 2023 | 7 | 2023 |
| How to train your heron A Richard, S Aravecchia, T Schillaci, M Geist, C Pradalier IEEE Robotics and Automation Letters 6 (3), 5247-5252, 2021 | 7 | 2021 |
| Graspldm: Generative 6-dof grasp synthesis using latent diffusion models KR Barad, A Orsula, A Richard, J Dentler, M Olivares-Mendez, C Martinez IEEE Access, 2024 | 5 | 2024 |
| RANS: Highly-Parallelised Simulator for Reinforcement Learning based Autonomous Navigating Spacecrafts M El-Hariry, A Richard, M Olivares-Mendez arXiv preprint arXiv:2310.07393, 2023 | 5 | 2023 |
| Enabling elements of simulations digital twins and its applicability for information superiority in defence domain K Aggarwal, E Bögel, M La Rosa Betancourt, M Collier-Wright, M Brake, ... Modelling and & Simulation Group (NMSG) Symposium 2022 STO-MP-MSG-197, 2022 | 5 | 2022 |
| Learning behaviors through physics-driven latent imagination A Richard, S Aravecchia, M Geist, C Pradalier Conference on Robot Learning, 1190-1199, 2022 | 4 | 2022 |
| A comprehensive benchmark of neural networks for system identification A Richard, A Mahé, C Pradalier, O Rozenstein, M Geist | 4 | 2019 |
| Automated segmentation of land use from overhead imagery A Richard, A Benbihi, C Pradalier, V Perez, R Van Couwenberghe International Conference on Precision Agriculture, 2018 | 4 | 2018 |
| Gps-aided visual wheel odometry J Song, PJ Sanchez-Cuevas, A Richard, M Olivares-Mendez 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 3 | 2023 |
| Performance Comparison of ROS2 Middlewares for Multi-robot Mesh Networks in Planetary Exploration LP Chovet, GM Garcia, A Bera, A Richard, K Yoshida, ... Journal of Intelligent & Robotic Systems 111 (1), 1-20, 2025 | 2 | 2025 |
| Object-centric Reconstruction and Tracking of Dynamic Unknown Objects using 3D Gaussian Splatting KR Barad, A Richard, J Dentler, M Olivares-Mendez, C Martinez arXiv preprint arXiv:2405.20104, 2024 | 2 | 2024 |
| Nvidia Omniverse for Active Space Debris Removal Missions, an Overview X Li, A Richard, OO Loumpasefski, BC Yalcin, C Martinez Luna, ... Clean Space Industry Days 2022, 2022 | 2 | 2022 |
| Importance sampling for deep system identification A Mahé, A Richard, B Mouscadet, C Pradalier, M Geist 2019 19Th International Conference on Advanced Robotics (ICAR), 43-48, 2019 | 2 | 2019 |
| A Deep Reinforcement Learning Framework and Methodology for Reducing the Sim-to-Real Gap in ASV Navigation LFW Batista, J Ro, A Richard, P Schroepfer, S Hutchinson, C Pradalier 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2024 | 1 | 2024 |
Prof. Cédric PradalierGeorgiaTech Lorraine, UMI2958 GT-CNRS, MetzΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα georgiatech-metz.fr