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» Spectral Clustering with Perturbed Data
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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...
SSPR
2010
Springer
13 years 6 months ago
Non-parametric Mixture Models for Clustering
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
ISCA
2007
IEEE
217views Hardware» more  ISCA 2007»
13 years 7 months ago
Parallel Processing of High-Dimensional Remote Sensing Images Using Cluster Computer Architectures
Hyperspectral sensors represent the most advanced instruments currently available for remote sensing of the Earth. The high spatial and spectral resolution of the images supplied ...
David Valencia, Antonio Plaza, Pablo Martín...
CBMS
2008
IEEE
14 years 2 months ago
ProtCV: A Tool for Extracting, Visualizing and Validating Protein Clusters Using Mass Spectra Peak-Lists
We present ProtCV (Protein Clustering and Visualization) a new software tool for grouping samples (mass spectra peak-lists) emanating from a high throughput proteomics analysis ba...
Stavroula Ventoura, Eugenia G. Giannopoulou, Elias...
CVPR
2009
IEEE
1133views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Sparse Subspace Clustering
We propose a method based on sparse representation (SR) to cluster data drawn from multiple low-dimensional linear or affine subspaces embedded in a high-dimensional space. Our ...
Ehsan Elhamifar, René Vidal