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DAGM
1998
Springer
13 years 10 months ago
Discrete Mixture Models for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
IDA
2009
Springer
14 years 23 days ago
Underdetermined Instantaneous Audio Source Separation via Local Gaussian Modeling
Underdetermined source separation is often carried out by modeling time-frequency source coefficients via a fixed sparse prior. This approach fails when the number of active sourc...
Emmanuel Vincent, Simon Arberet, Rémi Gribo...
CVPR
1999
IEEE
14 years 8 months ago
Deformable Template and Distribution Mixture-Based Data Modeling for the Endocardial Contour Tracking in an Echographic Sequence
We1 present a new method to shape-based segmentation of deformable anatomical structures in medical images and validate this approach by detecting and tracking the endocardial bor...
Max Mignotte, Jean Meunier
SADM
2010
141views more  SADM 2010»
13 years 29 days ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
CDC
2009
IEEE
149views Control Systems» more  CDC 2009»
13 years 7 months ago
Context-dependent multi-class classification with unknown observation and class distributions with applications to bioinformatic
We consider the multi-class classification problem, based on vector observation sequences, where the conditional (given class observations) probability distributions for each class...
Alex S. Baras, John S. Baras