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NIPS
2004
13 years 11 months ago
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Hyun-Jin Park, Te-Won Lee
NAACL
1994
13 years 11 months ago
High-Accuracy Large-Vocabulary Speech Recognition Using Mixture Tying and Consistency Modeling
Improved acoustic modeling can significantly decrease the error rate in large-vocabulary speech recognition. Our approach to the problem is twofold. We first propose a scheme that...
Vassilios Digalakis, Hy Murveit
BMCBI
2004
79views more  BMCBI 2004»
13 years 9 months ago
A new mixture model approach to analyzing allelic-loss data using Bayes factors
Background: Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor...
Manisha Desai, Mary J. Emond
VLSISP
1998
191views more  VLSISP 1998»
13 years 9 months ago
Image Compression Using KLT, Wavelets and an Adaptive Mixture of Principal Components Model
In this paper, we present preliminary results comparing the nature of the errors introduced by the mixture of principal components (MPC) model with a wavelet transform and the Karh...
Nanda Kambhatla, Simon Haykin, Robert D. Dony
AMDO
2006
Springer
14 years 1 months ago
Monocular Tracking with a Mixture of View-Dependent Learned Models
This paper considers the problem of monocular human body tracking using learned models. We propose to learn the joint probability distribution of appearance and body pose using a m...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...