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JMLR
2010
202views more  JMLR 2010»
14 years 5 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
CVPR
2012
IEEE
13 years 1 months ago
An online learned CRF model for multi-target tracking
We introduce an online learning approach for multitarget tracking. Detection responses are gradually associated into tracklets in multiple levels to produce final tracks. Unlike ...
Bo Yang, Ram Nevatia
CVPR
2012
IEEE
13 years 1 months ago
Large scale metric learning from equivalence constraints
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Martin Köstinger, Martin Hirzer, Paul Wohlhar...
CVPR
2009
IEEE
16 years 5 months ago
Learning query-dependent prefilters for scalable image retrieval
We describe an algorithm for similar-image search which is designed to be efficient for extremely large collections of images. For each query, a small response set is selected by...
Lorenzo Torresani (Dartmouth College), Martin Szum...
ICCV
2009
IEEE
1425views Computer Vision» more  ICCV 2009»
16 years 1 months ago
Fast Ray Features for Learning Irregular Shapes
We introduce a new class of image features, the Ray feature set, that consider image characteristics at distant contour points, capturing information which is difficult to repre...
Kevin Smith, Alan Carleton, Vincent Lepetit