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Publications of Samir Azrour
Articles in journal or book chapters
  1. Samir Azrour, Sébastien Piérard, and Marc Van Droogenbroeck. Defining a score based on gait analysis for the longitudinal follow-up of MS patient. Multiple Sclerosis Journal, 23(S11):408-409, September 2015. Note: Proceedings of ECTRIMS 2015 (Barcelona, Spain), P817. Keyword(s): GAIMS, Gait analysis, Multiple sclerosis, EDSS. [bibtex-entry]


  2. S. Piérard, S. Azrour, R. Phan-Ba, V. Delvaux, P. Maquet, and M. Van Droogenbroeck. Diagnosing multiple sclerosis with a gait measuring system, an analysis of the motor fatigue, and machine learning. Multiple Sclerosis Journal, 20(S1):171, September 2014. Note: Proceedings of ACTRIMS/ECTRIMS 2014 (Boston, USA), P232. Keyword(s): GAIMS, Multiple Sclerosis, Gait, Motor Fatigue. [bibtex-entry]


  3. S. Piérard, S. Azrour, R. Phan-Ba, and M. Van Droogenbroeck. GAIMS: A Reliable Non-Intrusive Gait Measuring System. ERCIM News, 95:26-27, October 2013. Keyword(s): Multiple Sclerosis, Gait, Outcome measure, GAIMS, Immersion, Machine learning. [bibtex-entry]


Conference articles
  1. Samir Azrour, Sébastien Piérard, Pierre Geurts, and Marc Van Droogenbroeck. A two-step methodology for human pose estimation increasing the accuracy and reducing the amount of learning samples dramatically. In Advanced Concepts for Intelligent Vision Systems (ACIVS), volume 10617 of Lecture Notes in Computer Science, pages 3-14, 2017. Keyword(s): Pose estimation, Orientation estimation. [bibtex-entry]


  2. Samir Azrour, Sébastien Piérard, and Marc Van Droogenbroeck. Improving pose estimation by building dedicated datasets and using orientation. In IET Workshop on Human Motion Analysis for Healthcare Applications, London, United Kingdom, May 2016. Keyword(s): Pose estimation, Human, Depth camera, 3D camera, Orientation. [bibtex-entry]


  3. Samir Azrour, Sébastien Piérard, and Marc Van Droogenbroeck. Leveraging orientation knowledge to enhance human pose estimation methods. In Articulated Motion and Deformable Objects AMDO, volume 9756 of Lecture Notes in Computer Science, Palma, Mallorca, Spain, pages 81-87, 2016. Springer. Keyword(s): Human pose estimation, Orientation, 3D, Machine learning. [bibtex-entry]


  4. Sébastien Piérard, Samir Azrour, and Marc Van Droogenbroeck. Slicing the 3D space into planes for the fast interpretation of human motion. In IET Workshop on Human Motion Analysis for Healthcare Applications, London, United Kingdom, May 2016. Keyword(s): Human, Motion, Gait analysis, GAIMS. [bibtex-entry]


  5. Samir Azrour, Sébastien Piérard, Pierre Geurts, and Marc Van Droogenbroeck. Data normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, pages 649-654, April 2014. Keyword(s): Data normalization, Machine learning, Multiple sclerosis. [bibtex-entry]


  6. S. Piérard, S. Azrour, R. Phan-Ba, and M. Van Droogenbroeck. Detection and characterization of gait modifications, for the longitudinal follow-up of patients with neurological diseases, based on the gait analyzing system GAIMS. In European Life Sciences Summit BIOMEDICA, Maastricht, The Netherlands, June 2014. Keyword(s): GAIMS, Gait, Follow-up, Patient, Multiple sclerosis. [bibtex-entry]


  7. S. Piérard, S. Azrour, and M. Van Droogenbroeck. Design of a reliable processing pipeling for the non-intrusive measurement of feet trajectories with lasers. In International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, pages 4399-4403, May 2014. Keyword(s): GAIMS, Feet, Multiple sclerosis. [bibtex-entry]


  8. Samir Azrour, Sébastien Piérard, and Marc Van Droogenbroeck. Using gait measuring system (GAIMS) to discriminate patients with multiple sclerosis from healthy persons. In BEMEKO Workshop on measurement: Challenges and Opportunities, Liège, Belgium, November 2013. [bibtex-entry]


  9. S. Piérard, S. Azrour, and M. Van Droogenbroeck. Measuring feet trajectories: challenges and applications. In BEMEKO Workshop on measurement: Challenges and Opportunities, Liège, Belgium, November 2013. Keyword(s): GAIMS, Feet, Tracking, Multiple sclerosis, Biometric identification. [bibtex-entry]


Miscellaneous
  1. Samir Azrour. Caractérisation des troubles de la marche par apprentissage automatique : détermination de scores adaptés à la sclérose en plaques à partir de données clinimétriques. Master's thesis, University of Liège, Belgium, June 2013. Keyword(s): TFE, GAIMS. [bibtex-entry]



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