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CVPR
2004
IEEE
16 years 8 months ago
Self-Normalized Linear Tests
Making decisions based on a linear combination L of features is of course very common in pattern recognition. For distinguishing between two hypotheses or classes, the test is of ...
Sachin Gangaputra, Donald Geman
CVPR
2006
IEEE
16 years 8 months ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman
ICPR
2008
IEEE
16 years 7 months ago
Visual features with semantic combination using Bayesian network for a more effective image retrieval
In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the use...
Sabine Barrat, Salvatore Tabbone
ICPR
2000
IEEE
16 years 7 months ago
Attributed Tree Homomorphism Using Association Graphs
The matching of hierarchical relational structures is of significant interest in computer vision and pattern recognition. We have recently introduced a new solution to this proble...
Massimo Bartoli, Marcello Pelillo, Kaleem Siddiqi,...
ICML
2006
IEEE
16 years 6 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey