98 search results - page 18 / 20 » On Point Sampling Versus Space Sampling for Dimensionality R... |
90
Voted
CVPR
2008
IEEE
16 years 3 months ago
2008
IEEE
Learning a discriminant becomes substantially more difficult when the datasets are high-dimensional and the available samples are few. This is often the case in computer vision an...
106
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CG
2006
Springer
15 years 1 months ago
2006
Springer
Connectivity and neighborhood are fundamental topological properties of objects in pictures. Since the input for any image analysis algorithm is a digital image, which does not ne...
157
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ESANN
2006
15 years 3 months ago
2006
The Self-Organizing map (SOM), a powerful method for data mining and cluster extraction, is very useful for processing data of high dimensionality and complexity. Visualization met...
125
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CVPR
2010
IEEE
15 years 10 months ago
2010
IEEE
Linear Discriminant Analysis (LDA) is a popular tool for multiclass discriminative dimensionality reduction. However, LDA suffers from two major problems: (1) It only optimizes th...
127
Voted
SMA
2003
ACM
15 years 7 months ago
2003
ACM
3D scanners developed over the past several decades have facilitated the reconstruction of complicated engineering parts. Typically the boundary representation of a part is recons...