23 search results - page 2 / 5 » Locality preserving constraints for super-resolution with ne... |
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
CVPR
2007
IEEE
13 years 11 months ago
2007
IEEE
We present the Conformal Embedding Analysis (CEA) for feature extraction and dimensionality reduction. Incorporating both conformal mapping and discriminating analysis, CEA projec...
GRC
2008
IEEE
13 years 6 months ago
2008
IEEE
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
NIPS
2003
13 years 6 months ago
2003
Spectral methods for nonlinear dimensionality reduction (NLDR) impose a neighborhood graph on point data and compute eigenfunctions of a quadratic form generated from the graph. W...
ICPR
2008
IEEE
13 years 11 months ago
2008
IEEE
In video surveillance, the size of face images is very small. However, few works have been done to investigate scale invariant face recognition. Our experiments on appearance-base...