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» Quantization of Sparse Representations
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IJON
2008
116views more  IJON 2008»
13 years 7 months ago
Discovering speech phones using convolutive non-negative matrix factorisation with a sparseness constraint
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...
Paul D. O'Grady, Barak A. Pearlmutter
ISBI
2011
IEEE
12 years 11 months ago
Sparse Riemannian manifold clustering for HARDI segmentation
We address the problem of segmenting high angular resolution diffusion images of the brain into cerebral regions corresponding to distinct white matter fiber bundles. We cast thi...
Hasan Ertan Çetingül, René Vida...
ICML
2007
IEEE
14 years 8 months ago
Bayesian compressive sensing and projection optimization
This paper introduces a new problem for which machine-learning tools may make an impact. The problem considered is termed "compressive sensing", in which a real signal o...
Shihao Ji, Lawrence Carin
SIAMIS
2008
211views more  SIAMIS 2008»
13 years 7 months ago
Sparse and Redundant Modeling of Image Content Using an Image-Signature-Dictionary
Modeling signals by sparse and redundant representations has been drawing considerable attention in recent years. Coupled with the ability to train the dictionary using signal exam...
Michal Aharon, Michael Elad
CVPR
2010
IEEE
14 years 3 months ago
Hierarchical Convolutional Sparse Image Decomposition
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew Zeiler, Dilip Krishnan, Graham Taylor, Rob...