| Wildland fire detection and monitoring using a drone-collected RGB/IR image dataset X Chen, B Hopkins, H Wang, L O’Neill, F Afghah, A Razi, P Fulé, J Coen, ... IEEE Access 10, 121301-121317, 2022 | 103 | 2022 |
| FLAME 2: Fire detection and modeLing: Aerial Multi-spectral imagE dataset B Hopkins, L O'Neill, F Afghah, A Razi, E Rowell, A Watts, P Fule, J Coen IEEE DataPort, 2023 | 23 | 2023 |
| 5G Wings: Investigating 5G-Connected Drones Performance in Non-Urban Areas M Gharib, B Hopkins, J Murrin, A Koka, F Afghah 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile …, 2023 | 6 | 2023 |
| Attention-guided synthetic data augmentation for drone-based wildfire detection J Boone, B Hopkins, F Afghah IEEE INFOCOM 2023-IEEE Conference on Computer Communications Workshops …, 2023 | 5 | 2023 |
| Pixels to pyrometrics: UAS-derived infrared imagery to evaluate and monitor prescribed fire behaviour and effects L O’Neill, PZ Fulé, A Watts, C Moran, B Hopkins, E Rowell, A Thode, ... International Journal of Wildland Fire 33 (11), 2024 | 1 | 2024 |
| FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management B Hopkins, L ONeill, M Marinaccio, E Rowell, R Parsons, S Flanary, ... arXiv preprint arXiv:2412.02831, 2024 | | 2024 |
| Training UAV Teams with Multi-Agent Reinforcement Learning Towards Fully 3D Autonomous Wildfire Response BA Hopkins Clemson University, 2024 | | 2024 |
