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» A Discriminative Framework for Modelling Object Classes
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CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
16 years 11 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
IWCM
2004
Springer
15 years 9 months ago
Tracking Complex Objects Using Graphical Object Models
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
CVPR
2007
IEEE
16 years 6 months ago
Flexible Object Models for Category-Level 3D Object Recognition
Today's category-level object recognition systems largely focus on fronto-parallel views of objects with characteristic texture patterns. To overcome these limitations, we pr...
Akash Kushal, Cordelia Schmid, Jean Ponce
CVPR
1999
IEEE
15 years 8 months ago
A New Bayesian Framework for Object Recognition
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. This approach provides an effici...
Yuri Boykov, Daniel P. Huttenlocher
VLDB
2007
ACM
147views Database» more  VLDB 2007»
16 years 4 months ago
A General Framework for Modeling and Processing Optimization Queries
An optimization query asks for one or more data objects that maximize or minimize some function over the data set. We propose a general class of queries, model-based optimization ...
Michael Gibas, Ning Zheng, Hakan Ferhatosmanoglu