| Recent advances in anomaly detection methods applied to aviation L Basora, X Olive, T Dubot Aerospace 6 (11), 117, 2019 | 102 | 2019 |
| Trajectory clustering of air traffic flows around airports X Olive, J Morio Aerospace Science and Technology 84, 776-781, 2019 | 69 | 2019 |
| Traffic, a toolbox for processing and analysing air traffic data X Olive Journal of Open Source Software 4 (39), 1518, 1-3, 2019 | 47 | 2019 |
| Bi-objective optimization of a multiple-target active debris removal mission N Bérend, X Olive Acta Astronautica 122, 324-335, 2016 | 46 | 2016 |
| Crowdsourced air traffic data from the OpenSky Network 2019–2020 M Strohmeier, X Olive, J Lübbe, M Schäfer, V Lenders Earth System Science Data 13 (2), 357-366, 2021 | 33 | 2021 |
| Deep trajectory clustering with autoencoders X Olive, L Basora, B Viry, R Alligier ICRAT 2020, 9th International Conference for Research in Air Transportation, 2020 | 33 | 2020 |
| Identifying anomalies in past en-route trajectories with clustering and anomaly detection methods X Olive, L Basora ATM Seminar 2019, 2019 | 30 | 2019 |
| Detecting controllers' actions in past mode S data by autoencoder-based anomaly detection X Olive, J Grignard, T Dubot, J Saint-Lot SID 2018, 8th SESAR Innovation Days, 2018 | 30 | 2018 |
| Detection and identification of significant events in historical aircraft trajectory data X Olive, L Basora Transportation Research Part C: Emerging Technologies 119, 102737, 2020 | 26 | 2020 |
| A python toolbox for processing air traffic data: A use case with trajectory clustering X Olive, L Basora 7th OpenSky Workshop 2019, 73-60, 2019 | 21 | 2019 |
| The aircraft runway scheduling problem: A survey S Ikli, C Mancel, M Mongeau, X Olive, E Rachelson Computers & Operations Research 132, 105336, 2021 | 20 | 2021 |
| Quantitative assessments of runway excursion precursors using Mode S data X Olive, P Bieber arXiv preprint arXiv:1903.11964, 2019 | 20 | 2019 |
| A-CDM Lite: Situation awareness and decision-making for small airports based on ADS-B data M Schultz, J Rosenow, X Olive 9th SESAR Innovation Days: Inspiring Long-Term Research in the Field of Air …, 2019 | 18 | 2019 |
| Aircraft fleet health monitoring with anomaly detection techniques L Basora, P Bry, X Olive, F Freeman Aerospace 8 (4), 103, 2021 | 17 | 2021 |
| Analysis of airport ground operations based on ADS-B data M Schultz, X Olive, J Rosenow, H Fricke, S Alam 2020 International Conference on Artificial Intelligence and Data Analytics …, 2020 | 15 | 2020 |
| Opensky report 2019: analysing tcas in the real world using big data M Schäfer, X Olive, M Strohmeier, M Smith, I Martinovic, V Lenders 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC), 1-9, 2019 | 13 | 2019 |
| Crowdsourced air traffic data from The OpenSky Network 2020 [CC-BY] X Olive, M Strohmeier, J Lübbe Zenodo, 2022 | 9 | 2022 |
| Data-driven airport management enabled by operational milestones derived from ADS-B messages M Schultz, J Rosenow, X Olive Journal of Air Transport Management 99, 102164, 2022 | 8 | 2022 |
| Detecting events in aircraft trajectories: Rule-based and data-driven approaches X Olive, J Sun, A Lafage, L Basora Proceedings 59 (1), 8, 2020 | 8 | 2020 |
| OpenSky report 2021: Insights on ads-b mandate and fleet deployment in times of crisis J Sun, X Olive, M Strohmeier, M Schäfer, I Martinovic, V Lenders 2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC), 1-10, 2021 | 7 | 2021 |
Martin StrohmeierSenior Scientist, Cyber-Defence Campus / Visiting Fellow, University of OxfordVerified email at cs.ox.ac.uk
