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» Is an ordinal class structure useful in classifier learning
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ICPR
2006
IEEE
14 years 8 months ago
Classifiers for Motion
In this paper we present a unsupervised learning based approach for sub-pixel motion estimation. The novelty of this work is the learning based method itself which tries to learn ...
Mithun Das Gupta, Nemanja Petrovic, ShyamSundar Ra...
ICIP
2003
IEEE
14 years 23 days ago
Image classification using multimedia knowledge networks
This paper presents novel methods for classifying images based on knowledge discovered from annotated images using WordNet. The novelty of this work is the automatic class discove...
Ana B. Benitez, Shih-Fu Chang
VMV
2008
107views Visualization» more  VMV 2008»
13 years 9 months ago
Learning with Few Examples using a Constrained Gaussian Prior on Randomized Trees
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...
Erik Rodner, Joachim Denzler
CVPR
2009
IEEE
15 years 2 months ago
Discriminative Structure Learning of Hierarchical Representations for Object Detection
A variety of flexible models have been proposed to detect objects in challenging real world scenes. Motivated by some of the most successful techniques, we propose a hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...
ICASSP
2011
IEEE
12 years 11 months ago
Maximum margin structure learning of Bayesian network classifiers
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
Franz Pernkop, Michael Wohlmay, Manfred Mücke