Hossain, H.M.S., Khan, M.A.A.H., Roy, N.: Active learning enabled activity recognition. In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. IEEE Access 7, 83600–83614 (2019)įan, W., Bouguila, N., Liu, X.: A hierarchical Dirichlet process mixture of GID distributions with feature selection for spatio-temporal video modeling and segmentation. 55, 125–136 (2016)įan, W., Bouguila, N.: Nonparametric hierarchical bayesian models for positive data clustering based on inverted Dirichlet-based distributions. In: ESANN (2016)Įpaillard, E., Bouguila, N.: Proportional data modeling with hidden Markov models based on generalized Dirichlet and beta-liouville mixtures applied to anomaly detection in public areas. Cambridge University Press (2004)ĭiethe, T., Twomey, N., Flach, P.A.: Active transfer learning for activity recognition. 41(5), 2329–2336 (2014)īourouis, S., Al-Osaimi, F.R., Bouguila, N., Sallay, H., Aldosari, F., Al Mashrgy, M.: Bayesian inference by reversible jump MCMC for clustering based on finite generalized inverted Dirichlet mixtures. 277–282 (2014)īourouis, S., Al Mashrgy, M., Bouguila, N.: Bayesian learning of finite generalized inverted Dirichlet mixtures: application to object classification and forgery detection. In: 2014 1st International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), pp.
Springer (2006)īouguila, N.: A model-based discriminative framework for sets of positive vectors classification: application to object categorization. Bdiri, T., Bouguila, N., Ziou, D.: Variational bayesian inference for infinite generalized inverted Dirichlet mixtures with feature selection and its application to clustering.
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