468 search results - page 20 / 94 » Riemannian Manifold Learning |
103
Voted
AAAI
2008
15 years 2 months ago
2008
Most manifold learning methods consider only one similarity matrix to induce a low-dimensional manifold embedded in data space. In practice, however, we often use multiple sensors...
108
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ICIP
2005
IEEE
16 years 1 months ago
2005
IEEE
A new approach to active contours on statistical manifolds is presented. The statistical manifolds are 2dimensional Riemannian manifolds that are statistically defined by maps that...
ICPR
2010
IEEE
14 years 9 months ago
2010
IEEE
Unlike most previous manifold-based data classification algorithms assume that all the data points are on a single manifold, we expect that data from different classes may reside ...
CVPR
2008
IEEE
16 years 1 months ago
2008
IEEE
Given a finite number of data points sampled from a low-dimensional manifold embedded in a high dimensional space together with the parameter vectors for a subset of the data poin...
111
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ICASSP
2011
IEEE
14 years 3 months ago
2011
IEEE
The construction of low-dimensional models explaining highdimensional signal observations provides concise and efficient data representations. In this paper, we focus on pattern ...