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» Explanation-Based Learning for Image Understanding
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ICCV
2009
IEEE
13 years 5 months ago
Image annotation using multi-label correlated Green's function
Image annotation has been an active research topic in the recent years due to its potentially large impact on both image understanding and web/database image search. In this paper...
Hua Wang, Heng Huang, Chris H. Q. Ding
ESANN
2006
13 years 9 months ago
Learning Visual Invariance
Invariance is a necessary feature of a visual system able to recognize real objects in all their possible appearance. It is also the processing step most problematic to understand ...
Alessio Plebe
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 8 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
ICMLA
2009
13 years 5 months ago
Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Johannes Hartz
ICPR
2006
IEEE
14 years 8 months ago
Fast, Illumination Insensitive Face Detection Based on Multilinear Techniques and Curvature Features
This paper brings together two recent developments in image analysis. We consider a new mathematical framework that provides illumination invariant descriptors for face detection....
Christian Bauckhage, Thomas Käster