Sciweavers

45 search results - page 2 / 9
» Computing Gaussian Mixture Models with EM Using Equivalence ...
Sort
View
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 4 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
ICPR
2010
IEEE
13 years 2 months ago
Information Theoretic Expectation Maximization Based Gaussian Mixture Modeling for Speaker Verification
The expectation maximization (EM) algorithm is widely used in the Gaussian mixture model (GMM) as the state-of-art statistical modeling technique. Like the classical EM method, th...
Sheeraz Memon, Margaret Lech, Namunu Chinthaka Mad...
EMMCVPR
1999
Springer
13 years 9 months ago
On Fitting Mixture Models
Consider the problem of tting a nite Gaussian mixture, with an unknown number of components, to observed data. This paper proposes a new minimum description length (MDL) type crite...
Mário A. T. Figueiredo, José M. N. L...
CVPR
2007
IEEE
14 years 6 months ago
Combining Region and Edge Cues for Image Segmentation in a Probabilistic Gaussian Mixture Framework
In this paper we propose a new segmentation algorithm which combines patch-based information with edge cues under a probabilistic framework. We use a mixture of multiple Gaussians...
Omer Rotem, Hayit Greenspan, Jacob Goldberger
ACCV
2007
Springer
13 years 11 months ago
Image Segmentation Using Co-EM Strategy
Inspired by the idea of multi-view, we proposed an image segmentation algorithm using co-EM strategy in this paper. Image data are modeled using Gaussian Mixture Model (GMM), and t...
Zhenglong Li, Jian Cheng, Qingshan Liu, Hanqing Lu