332 search results - page 27 / 67 » On the Performance of Chernoff-Distance-Based Linear Dimensi... |
ICIAR
2004
Springer
15 years 5 months ago
2004
Springer
Previous work has shown that principal component analysis (PCA) of three-dimensional face models can be used to perform recognition to a high degree of accuracy. However, experimen...
CVPR
2005
IEEE
16 years 1 months ago
2005
IEEE
We present a novel multilinear algebra based approach for reduced dimensionality representation of image ensembles. We treat an image as a matrix, instead of a vector as in tradit...
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KDD
2005
ACM
16 years 6 days ago
2005
ACM
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
DAGM
2006
Springer
15 years 3 months ago
2006
Springer
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....
ICONIP
2007
15 years 1 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...