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2023
1 Murray, Brian; Bellingmo, Pauline Røstum; Hagaseth, Marianne; Lied, Thorbjørn Tønnesen.
Autoencoder-Based Anomaly Detection for Safe Autonomous Ship Operations. The 33rd European Safety and Reliability Conference (ESREL 2023); 2023-09-03 - 2023-09-07
OCEAN Untitled
 
2 Murray, Brian; Bellingmo, Pauline Røstum; Hagaseth, Marianne; Lied, Thorbjørn Tønnesen.
Supporting Remote Operation Centres for Unmanned Ships Through Machine Learning- Based Route Prediction. International Conference on Maritime Autonomous Surface Ships (ICMASS); 2023-11-08 - 2023-11-09
OCEAN Untitled
 
3 Murray, Brian; Bellingmo, Pauline Røstum; Lied, Thorbjørn Tønnesen; Hagaseth, Marianne.
Autoencoder-Based Anomaly Detection for Safe Autonomous Ship Operations. I: Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023). Research Publishing Services 2023 ISBN 978-981-18-8071-1.
OCEAN Untitled
 
4 Murray, Brian; Wennersberg, Lars Andreas Lien; Johnsen, Stig Ole.
En «KI-kaptein» på fregatten ville neppe unngått kollisjon. Dagens næringsliv 2023
OCEAN SINTEF Untitled
 
5 Tritsarolis, Andreas; Murray, Brian; Pelekis, Nikos; Theodoridis, Yannis.
Collision Risk Assessment and Forecasting on Maritime Data. I: Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems. Association for Computing Machinery (ACM) 2023 ISBN 979-8-4007-0168-9. s. -
OCEAN Untitled
 
2022
6 Berge, Svein Peder; Bellingmo, Pauline Røstum; Murray, Brian; Jørgensen, Ulrik; Rørhus, Ole Georg; Pobitzer, Armin.
Evaluation of Ship Energy Models and Route Optimization. 21st International Conference on Computer and IT Applications in the Maritime Industries, COMPIT’22; 2022-06-21 - 2022-06-23
SINTEF OCEAN Untitled
 
7 Berge, Svein Peder; Jørgensen, Ulrik; Murray, Brian; Pobitzer, Armin; Rørhus, Ole Georg.
Evaluation of Ship Energy Models and Route Optimization. I: 21st International Conference on Computer and IT Applications in the Maritime Industries - COMPIT’22. Technische Universität Hamburg-Harburg 2022 ISBN 978-978-38922-0-0.
OCEAN SINTEF Untitled
 
8 Hagaseth, Marianne; Rødseth, Ørnulf Jan; Meland, Per HÃ¥kon; Wille, Egil; Murray, Brian; Meling, Pia.
Methodology for Approval of Autonomous Ship System CONOPS. COMPIT’22 - 21 st Conference on Computer and IT Applications in the Maritime Industrie; 2022-06-21 - 2022-06-23
OCEAN SINTEF Untitled
 
9 Jørgensen, Ulrik; Bellingmo, Pauline Røstum; Murray, Brian; Berge, Svein Peder; Pobitzer, Armin.
Ship Route Optimization Using Hybrid Physics-Guided Machine Learning. Journal of Physics: Conference Series (JPCS) 2022 ;Volum 2311. s. -
OCEAN SINTEF Untitled
 
10 Jørgensen, Ulrik; Bellingmo, Pauline Røstum; Murray, Brian; Berge, Svein Peder; Pobitzer, Armin.
Ship Route Optimization Using Hybrid Physics-Guided Machine Learning. MTEC-ICMASS 2022; 2022-04-04 - 2022-04-06
OCEAN SINTEF Untitled
 
11 Murray, Brian; Rødseth, Ørnulf Jan; Nordahl, Håvard; Wennersberg, Lars Andreas Lien; Pobitzer, Armin; Foss, Henrik.
Approvable AI for Autonomous Ships: Challenges and Possible Solutions. I: Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022). Research Publishing Services 2022 ISBN 978-981-18-5183-4. s. 1-8
OCEAN SINTEF Untitled
 
2021
12 Murray, Brian; Perera, Lokukaluge Prasad.
An AIS-based deep learning framework for regional ship behavior prediction. Reliability Engineering & System Safety 2021 ;Volum 215. s. -
UiT Untitled
 
13 Murray, Brian; Perera, Lokukaluge Prasad.
Deep Representation Learning-Based Vessel Trajectory Clustering for Situation Awareness in Ship Navigation. I: Maritime Technology and Engineering 5. CRC Press 2021 ISBN 9780367773748.
UiT OCEAN Untitled
 
14 Murray, Brian; Perera, Lokukaluge Prasad.
Proactive Collision Avoidance for Autonomous Ships: Leveraging Machine Learning to Emulate Situation Awareness. IFAC-PapersOnLine 2021 ;Volum 54.(16) s. 16-23
UiT OCEAN Untitled
 
15 Murray, Brian; Perera, Lokukaluge Prasad.
Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness. Journal of Ocean Engineering and Science 2021 s. 1-16
UiT Untitled
 
16 Murray, Brian.
Machine Learning for Enhanced Maritime Situation Awareness - Leveraging Historical AIS Data for Ship Trajectory Prediction (PhD Thesis). Tromsø: UiT The Arctic University of Norway 2021 186 s.
NTNU UiT Untitled
 
2020
17 Murray, Brian; Perera, Lokukaluge Prasad.
A dual linear autoencoder approach for vessel trajectory prediction using historical AIS data. Ocean Engineering 2020
UiT Untitled
 
18 Murray, Brian; Perera, Lokukaluge Prasad.
Unsupervised Trajectory Anomaly Detection for Situation Awareness in Maritime Navigation. I: ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering - Volume 6A: Ocean Engineering. The American Society of Mechanical Engineers (ASME) 2020 ISBN 978-0-7918-8437-9.
UiT Untitled
 
2019
19 Murray, Brian; Perera, Lokukaluge Prasad.
An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels. I: ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. Volume 7B: Ocean Engineering. The American Society of Mechanical Engineers (ASME) 2019 ISBN 978-0-7918-5885-1. s. -
UiT Untitled
 
20 Perera, Lokukaluge Prasad; Murray, Brian.
Situation Awareness of Autonomous Ship Navigation in a Mixed Environment under Advanced Ship Predictor. I: ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. Volume 7B: Ocean Engineering. The American Society of Mechanical Engineers (ASME) 2019 ISBN 978-0-7918-5885-1.
UiT Untitled
 
2018
21 Murray, Brian; Perera, Lokukaluge Prasad.
A data-driven approach to vessel trajectory prediction for safe autonomous ship operations. I: Thirteenth International Conference on Digital Information Management (ICDIM). IEEE (Institute of Electrical and Electronics Engineers) 2018 ISBN 978-1-5386-5244-2. s. 240-247
UiT Untitled
 
2017
22 Sollid, Magne-Petter; Murray, Brian.
Navigational Challenges in the Spitsbergen Area. I: SARex2 : Surviving a maritime incident in cold climate conditions. Rapporter fra Universitetet i Stavanger;69: Stavanger: Universitet i Stavanger 2017 ISBN 978-82-7644-747-7. s. 208-216
UiT Untitled