91 search results - page 17 / 19 » Non-linear Dimensionality Reduction by Locally Linear Isomap... |
ICIP
2007
IEEE
14 years 9 months ago
2007
IEEE
Image segmentation with shape priors has received a lot of attention over the past years. Most existing work focuses on a linearized shape space with small deformation modes aroun...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
ICIP
2007
IEEE
13 years 11 months ago
2007
IEEE
The major problem in building a good lipreading system is to extract effective visual features from enormous quantity of video sequences data. For appearance-based feature analysi...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
ESANN
2007
13 years 9 months ago
2007
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...