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IJON
2007
114views more  IJON 2007»
15 years 7 months ago
Ridgelet kernel regression
In this paper, a ridgelet kernel regression model is proposed for approximation of high dimensional functions. It is based on ridgelet theory, kernel and regularization technology ...
Shuyuan Yang, Min Wang, Licheng Jiao
JMIV
2007
115views more  JMIV 2007»
15 years 7 months ago
Combining Points and Tangents into Parabolic Polygons
Image and geometry processing applications estimate the local geometry of objects using information localized at points. They usually consider information about the tangents as a s...
Marcos Craizer, Thomas Lewiner, Jean-Marie Morvan
SIAMIS
2010
116views more  SIAMIS 2010»
15 years 5 months ago
Higher-Order Feature-Preserving Geometric Regularization
We introduce two fourth-order regularization methods that remove geometric noise without destroying significant geometric features. These methods leverage ideas from image denoisi...
Marc Droske, Andrea Bertozzi
CVPR
2012
IEEE
13 years 9 months ago
Pose pooling kernels for sub-category recognition
The ability to normalize pose based on super-category landmarks can significantly improve models of individual categories when training data are limited. Previous methods have co...
Ning Zhang, Ryan Farrell, Trevor Darrell
ICCV
2009
IEEE
17 years 5 days ago
Dimensionality Reduction and Principal Surfaces via Kernel Map Manifolds
We present a manifold learning approach to dimensionality reduction that explicitly models the manifold as a mapping from low to high dimensional space. The manifold is represen...
Samuel Gerber, Tolga Tasdizen, Ross Whitaker