| An AIS-based deep learning framework for regional ship behavior prediction B Murray, LP Perera Reliability Engineering & System Safety 215, 107819, 2021 | 166 | 2021 |
| A dual linear autoencoder approach for vessel trajectory prediction using historical AIS data B Murray, LP Perera Ocean engineering 209, 107478, 2020 | 146 | 2020 |
| Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness B Murray, LP Perera Journal of Ocean Engineering and Science 7 (1), 1-13, 2022 | 79 | 2022 |
| A data-driven approach to vessel trajectory prediction for safe autonomous ship operations B Murray, LP Perera 2018 Thirteenth International Conference on Digital Information Management …, 2018 | 57 | 2018 |
| An AIS-based multiple trajectory prediction approach for collision avoidance in future vessels B Murray, LP Perera International Conference on Offshore Mechanics and Arctic Engineering 58851 …, 2019 | 31 | 2019 |
| Situation awareness of autonomous ship navigation in a mixed environment under advanced ship predictor LP Perera, B Murray international conference on offshore mechanics and arctic engineering 58851 …, 2019 | 26 | 2019 |
| Proactive collision avoidance for autonomous ships: Leveraging machine learning to emulate situation awareness B Murray, LP Perera IFAC-PapersOnLine 54 (16), 16-23, 2021 | 13 | 2021 |
| Approvable AI for autonomous ships: Challenges and possible solutions B Murray, OJ Rødseth, H Nordahl, LAL Wennersberg, A Pobitzer, H Foss Proceedings of the 32nd European Safety and Reliability Conference (ESREL …, 2022 | 9 | 2022 |
| Deep representation learning-based vessel trajectory clustering for situation awareness in ship navigation B Murray, LP Perera Maritime Technology and Engineering 5 Volume 1, 157-165, 2021 | 6 | 2021 |
| Unsupervised trajectory anomaly detection for situation awareness in maritime navigation B Murray, LP Perera International Conference on Offshore Mechanics and Arctic Engineering 84379 …, 2020 | 6 | 2020 |
| Ship route optimization using hybrid physics-guided machine learning U Jørgensen, PR Belingmo, B Murray, SP Berge, A Pobitzer Journal of Physics: Conference Series 2311 (1), 012037, 2022 | 5 | 2022 |
| Collision risk assessment and forecasting on maritime data A Tritsarolis, B Murray, N Pelekis, Y Theodoridis Proceedings of the 31st ACM International Conference on Advances in …, 2023 | 4 | 2023 |
| Machine Learning for Enhanced Maritime Situation Awareness: Leveraging Historical AIS Data for Ship Trajectory Prediction B Murray UiT Norges arktiske universitet, 2021 | 4 | 2021 |
| Autoen-coder-based anomaly detection for safe autonomous ship operations [C] B Murray, PR Bellingmo, TT Lied, M Hagaseth The 33 th European Safety and Reliability Conference (ESREL2023 …, 2023 | 3 | 2023 |
| Data-driven construction of maritime traffic networks for AI-based route prediction V Hoffmann, JH Webert, B Murray, R Graf Journal of Physics: Conference Series 2867 (1), 012048, 2024 | 1 | 2024 |
| Project type: IA Innovation Action Start of the project: 01/06/2019 Duration: 54 months AL Wennersberg, B Murray, M Ragnes, T Hals, TJ Vatnehol, J Nymoen, ... | | |
| Autonomous Ships: Leveraging Machine Learning to Emulate Situation Awareness B Murray, LP Perera | | |
| Evaluation of Ship Energy Models and Route Optimization PR Bellingmo, B Murray, U Jørgensen, A Pobitzer, SP Berge, OG Rørhus | | |
