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TNN
2010
216views Management» more  TNN 2010»
13 years 2 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
ISBI
2008
IEEE
14 years 8 months ago
Level set segmentation of dermoscopy images
This paper presents a method for the segmentation of skin lesions in dermoscopy images. The proposed technique uses region based level sets and adopts a mixture of Gaussian densit...
Margarida Silveira, Jorge S. Marques
ICASSP
2009
IEEE
14 years 2 months ago
Joint map adaptation of feature transformation and Gaussian Mixture Model for speaker recognition
This paper extends our previous work on feature transformationbased support vector machines for speaker recognition by proposing a joint MAP adaptation of feature transformation (...
Donglai Zhu, Bin Ma, Haizhou Li
ICCV
2003
IEEE
14 years 9 months ago
Inferring 3D Structure with a Statistical Image-Based Shape Model
We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure" model. The 3D shape of an object class is represented by sets...
Kristen Grauman, Gregory Shakhnarovich, Trevor Dar...
ICPR
2010
IEEE
14 years 2 months ago
Dimension-Decoupled Gaussian Mixture Model for Short Utterance Speaker Recognition
The Gaussian Mixture Model (GMM) is often used in conjunction with Mel-frequency cepstral coefficient (MFCC) feature vectors for speaker recognition. A great challenge is to use ...
Thilo Stadelmann, Bernd Freisleben