207 search results - page 10 / 42 » Regularized Principal Manifolds |
ICCV
2007
IEEE
14 years 2 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
ECCV
2004
Springer
14 years 1 months ago
2004
Springer
Diffusion tensor magnetic resonance imaging (DT-MRI) is emerging as an important tool in medical image analysis of the brain. However, relatively little work has been done on produ...
JMLR
2010
13 years 2 months ago
2010
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...
VMV
2000
13 years 9 months ago
2000
Anisotropic diffusion is known to be a powerful tool in image processing. It enables the smoothing of initially noisy images while still retaining, respectively sharpening edges a...
FTML
2010
13 years 6 months ago
2010
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...