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» Learning Visual Invariance
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GFKL
2007
Springer
164views Data Mining» more  GFKL 2007»
14 years 1 months ago
Classification with Invariant Distance Substitution Kernels
Kernel methods offer a flexible toolbox for pattern analysis and machine learning. A general class of kernel functions which incorporates known pattern invariances are invariant d...
Bernard Haasdonk, Hans Burkhardt
APLAS
2010
ACM
13 years 10 months ago
Automatically Inferring Quantified Loop Invariants by Algorithmic Learning from Simple Templates
Abstract. By combining algorithmic learning, decision procedures, predicate abstraction, and simple templates, we present an automated technique for finding quantified loop invaria...
Soonho Kong, Yungbum Jung, Cristina David, Bow-Yaw...
ICASSP
2011
IEEE
13 years 1 months ago
Log-gaussian cox processes of visual keypoints for sonar texture recognition
In this paper, invariant sonar texture characterization for seabed classification is addressed from the spatial distribution of image keypoints using log-Gaussian Cox processes. ...
Huu-Giao Nguyen, Ronan Fablet, Jean-Marc Boucher
ICPR
2006
IEEE
14 years 11 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
CVPR
2007
IEEE
14 years 12 months ago
Robust Click-Point Linking: Matching Visually Dissimilar Local Regions
This paper presents robust click-point linking: a novel localized registration framework that allows users to interactively prescribe where the accuracy has to be high. By emphasi...
Kazunori Okada, Xiaolei Huang