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» Learning Object Shape: From Drawings to Images
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DAGM
2006
Springer
15 years 10 months ago
Nonparametric Density Estimation for Human Pose Tracking
The present paper considers the supplement of prior knowledge about joint angle configurations in the scope of 3-D human pose tracking. Training samples obtained from an industrial...
Thomas Brox, Bodo Rosenhahn, Uwe G. Kersting, Dani...
ICML
2009
IEEE
16 years 7 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
ICIP
1999
IEEE
16 years 8 months ago
Uncertainties in Bayesian Geometric Models
Deformable geometric models fit very naturally into the context of Bayesian analysis. The prior probability of boundary shapes is taken to proportional to the negative exponential...
Kenneth M. Hanson, Gregory S. Cunningham, Robert J...
NIPS
2008
15 years 7 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
ICWL
2004
Springer
15 years 11 months ago
Learning Algorithms with an Electronic Chalkboard over the Web
This paper describes a system for the animation of algorithms on an electronic chalkboard. The instructor teaching an algorithm can enter data directly through a drawing- the algor...
Margarita Esponda Argüero, Raúl Rojas