| Physical human activity recognition using wearable sensors F Attal, S Mohammed, M Dedabrishvili, F Chamroukhi, L Oukhellou, ... Sensors 15 (12), 31314-31338, 2015 | 919 | 2015 |
| Clustering smart card data for urban mobility analysis K Mohamed, E Côme, L Oukhellou, M Verleysen IEEE Transactions on intelligent transportation systems 18 (3), 712-728, 2016 | 258 | 2016 |
| Model-based count series clustering for bike sharing system usage mining: a case study with the Vélib’system of Paris C Etienne, O Latifa ACM Transactions on Intelligent Systems and Technology (TIST) 5 (3), 1-21, 2014 | 245 | 2014 |
| Analyzing year-to-year changes in public transport passenger behaviour using smart card data AS Briand, E Côme, M Trépanier, L Oukhellou Transportation Research Part C: Emerging Technologies 79, 274-289, 2017 | 221 | 2017 |
| An unsupervised approach for automatic activity recognition based on hidden Markov model regression D Trabelsi, S Mohammed, F Chamroukhi, L Oukhellou, Y Amirat IEEE Transactions on automation science and engineering 10 (3), 829-835, 2013 | 219 | 2013 |
| Fault diagnosis in railway track circuits using Dempster–Shafer classifier fusion L Oukhellou, A Debiolles, T Denœux, P Aknin Engineering Applications of Artificial Intelligence 23 (1), 117-128, 2010 | 154 | 2010 |
| Learning from partially supervised data using mixture models and belief functions E Côme, L Oukhellou, T Denoeux, P Aknin Pattern recognition 42 (3), 334-348, 2009 | 149 | 2009 |
| Forecasting dynamic public transport origin-destination matrices with long-short term memory recurrent neural networks F Toqué, E Côme, MK El Mahrsi, L Oukhellou 2016 IEEE 19th international conference on intelligent transportation …, 2016 | 136 | 2016 |
| Joint segmentation of multivariate time series with hidden process regression for human activity recognition F Chamroukhi, S Mohammed, D Trabelsi, L Oukhellou, Y Amirat Neurocomputing 120, 633-644, 2013 | 121 | 2013 |
| Short & long term forecasting of multimodal transport passenger flows with machine learning methods F Toqué, M Khouadjia, E Come, M Trepanier, L Oukhellou 2017 IEEE 20th International Conference on Intelligent Transportation …, 2017 | 101 | 2017 |
| Spatiotemporal analysis of bluetooth data: Application to a large urban network PA Laharotte, R Billot, E Come, L Oukhellou, A Nantes, NE El Faouzi IEEE Transactions on Intelligent Transportation Systems 16 (3), 1439-1448, 2014 | 98 | 2014 |
| Data-driven based approach to aid Parkinson’s disease diagnosis N Khoury, F Attal, Y Amirat, L Oukhellou, S Mohammed Sensors 19 (2), 242, 2019 | 96 | 2019 |
| Fuel cells static and dynamic characterizations as tools for the estimation of their ageing time R Onanena, L Oukhellou, D Candusso, F Harel, D Hissel, P Aknin International Journal of Hydrogen Energy 36 (2), 1730-1739, 2011 | 82 | 2011 |
| Recognition of gait cycle phases using wearable sensors S Mohammed, A Same, L Oukhellou, K Kong, W Huo, Y Amirat Robotics and Autonomous Systems 75, 50-59, 2016 | 80 | 2016 |
| A mixture model clustering approach for temporal passenger pattern characterization in public transport AS Briand, E Côme, MK El Mahrsi, L Oukhellou International Journal of Data Science and Analytics 1, 37-50, 2016 | 70 | 2016 |
| Understanding passenger patterns in public transit through smart card and socioeconomic data K Mohamed, E Côme, J Baro, L Oukhellou UrbComp, Seattle, WA, USA, 2014 | 67 | 2014 |
| Paramétrisation et classification de signaux en contrôle non destructif. Application à la reconnaissance des défauts de rails par courants de Foucault L Oukhellou Université Paris Sud-Paris XI, 1997 | 51 | 1997 |
| Spatio-temporal analysis of dynamic origin-destination data using latent dirichlet allocation: Application to vélib'bike sharing system of paris E Come, NA Randriamanamihaga, L Oukhellou, P Aknin TRB 93rd Annual meeting, 19p, 2014 | 50 | 2014 |
| Combined use of sensor data and structural knowledge processed by Bayesian network: Application to a railway diagnosis aid scheme L Oukhellou, E Come, L Bouillaut, P Aknin Transportation Research Part C: Emerging Technologies 16 (6), 755-767, 2008 | 50 | 2008 |
| A dedicated mixture model for clustering smart meter data: identification and analysis of electricity consumption behaviors FN Melzi, A Same, MH Zayani, L Oukhellou Energies 10 (10), 1446, 2017 | 48 | 2017 |
Etienne CômeGustave Eiffel University在 univ-eiffel.fr 的电子邮件经过验证
