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» Combining Gaussian Mixture Models
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KDD
2003
ACM
191views Data Mining» more  KDD 2003»
14 years 9 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 8 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
PRL
2007
154views more  PRL 2007»
13 years 8 months ago
Regularized mixture discriminant analysis
Abstract – In this paper we seek a Gaussian mixture model (GMM) of the classconditional densities for plug-in Bayes classification. We propose a method for setting the number of ...
Zohar Halbe, Mayer Aladjem
AVSS
2009
IEEE
14 years 10 days ago
Bayesian Bio-inspired Model for Learning Interactive Trajectories
—Automatic understanding of human behavior is an important and challenging objective in several surveillance applications. One of the main problems of this task consists in accur...
Alessio Dore, Carlo S. Regazzoni
CVPR
2007
IEEE
14 years 29 days ago
On the Performance Prediction and Validation for Multisensor Fusion
Multiple sensors are commonly fused to improve the detection and recognition performance of computer vision and pattern recognition systems. The traditional approach to determine ...
Rong Wang, Bir Bhanu