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Exploration de données de traçabilité issues de la RFID par apprentissage non-supervisé.

, , and . EGC, volume RNTI-E-15 of Revue des Nouvelles Technologies de l'Information, page 451-452. Cépaduès-Éditions, (2009)

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Topographic Connectionist Unsupervised Learning for RFID Behavior Data Mining., , , and . IWRT, page 63-72. INSTICC PRESS, (2008)LEA2C: Low Energy Adaptive Connectionist Clustering for Wireless Sensor Networks., , and . MATA, volume 3744 of Lecture Notes in Computer Science, page 405-415. Springer, (2005)Learning Topological Constraints in Self-Organizing Map., and . ICONIP (2), volume 6444 of Lecture Notes in Computer Science, page 367-374. Springer, (2010)Réduction des dimensions des données en apprentissage artificiel., , and . AAFD, volume A-2 of RNTI, page 135-165. Cépaduès-Éditions, (2006)Quantum Semi Non-negative Matrix Factorization., , , and . SoCPaR, volume 1383 of Advances in Intelligent Systems and Computing, page 135-144. Springer, (2020)On the use of TDNN-extracted features information in talker identification., and . ICASSP, page 385-388. IEEE Computer Society, (1991)Collaborative Random Forests Learning., , and . HPCC/DSS/SmartCity/DependSys, page 1147-1154. IEEE, (2021)Incremental Unsupervised Domain Adaptation Through Optimal Transport., , and . IJCNN, page 1-8. IEEE, (2022)Discriminative feature extraction and selection applied to face recognition., and . IJCNN, page 3291-3294. IEEE, (1999)Modular Self-Supervised Learning for Hand Surgical Diagnosis., , , , , and . IJCNN, page 1-8. IEEE, (2023)