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» Invariances in kernel methods: From samples to objects
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ICPR
2006
IEEE
14 years 6 months ago
Graph-based transformation manifolds for invariant pattern recognition with kernel methods
We present here an approach for applying the technique of modeling data transformation manifolds for invariant learning with kernel methods. The approach is based on building a ke...
Alexei Pozdnoukhov, Samy Bengio
ICCV
2009
IEEE
13 years 3 months ago
Group-sensitive multiple kernel learning for object categorization
In this paper, we propose a group-sensitive multiple kernel learning (GS-MKL) method to accommodate the intra-class diversity and the inter-class correlation for object categoriza...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...
SSPR
1998
Springer
13 years 9 months ago
Object Recognition from Large Structural Libraries
This paper presents a probabilistic similarity measure for object recognition from large libraries of line-patterns. We commence from a structural pattern representation which use...
Benoit Huet, Edwin R. Hancock
ICCV
2001
IEEE
14 years 7 months ago
Robust Histogram Construction from Color Invariants
An effective object recognition scheme is to represent and match images on the basis of histograms derived from photometric color invariants. A drawback, however, is that certain c...
Theo Gevers
ICML
2008
IEEE
14 years 6 months ago
Graph kernels between point clouds
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
Francis R. Bach