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Base de données de capteurs à localisation mobile Modèle et langage.

, , , and . Ingénierie des Systèmes d Inf., 14 (5): 35-58 (2009)

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MRI brain tumor classification using Support Vector Machines and meta-heuristic method., , and . ISDA, page 446-451. IEEE, (2015)Characterizing Traffic Density and Its Evolution through Moving Object Trajectories., , , and . SITIS, page 257-263. IEEE Computer Society, (2009)Characterizing the Traffic Density and Its Evolution through Moving Object Trajectories., , , and . KDIR, page 319-322. INSTICC Press, (2009)Classification of brain tumors using personalized deep belief networks on MRImages: PDBN-MRI., and . ICMV, volume 11041 of SPIE Proceedings, page 110412M. SPIE, (2018)Characterizing the Traffic Density and Its Evolution through Moving Object Trajectories., , , and . KDIR, page 319-322. INSTICC Press, (2009)Clustering Algorithm for Network Constraint Trajectories., , , and . SDH, page 631-647. Springer, (2008)Base de données de capteurs à localisation mobile Modèle et langage., , , and . Ingénierie des Systèmes d Inf., 14 (5): 35-58 (2009)A Hybrid Feature Selection for MRI Brain Tumor Classification., and . IBICA, volume 735 of Advances in Intelligent Systems and Computing, page 329-338. Springer, (2017)Caractérisation de la densité de trafic et de son évolution à partir de trajectoires d'objets mobiles., , , and . UbiMob, volume 394 of ACM International Conference Proceeding Series, page 33-40. ACM, (2009)