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146
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PR
2011
14 years 5 months ago
A survey of multilinear subspace learning for tensor data
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
159
Voted
CVPR
2009
IEEE
16 years 10 months ago
Visual Tracking with Online Multiple Instance Learning
In this paper, we address the problem of learning an adaptive appearance model for object tracking. In particular, a class of tracking techniques called “tracking by detection...
Boris Babenko, Ming-Hsuan Yang, Serge J. Belongie
143
Voted
CVPR
2009
IEEE
16 years 10 months ago
Learning Invariant Features Through Topographic Filter Maps
Several recently-proposed architectures for highperformance object recognition are composed of two main stages: a feature extraction stage that extracts locallyinvariant feature...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergu...
134
Voted
CVPR
2007
IEEE
16 years 4 months ago
Learning the Compositional Nature of Visual Objects
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Björn Ommer, Joachim M. Buhmann
155
Voted
ICMCS
2008
IEEE
207views Multimedia» more  ICMCS 2008»
15 years 9 months ago
Structure learning in a Bayesian network-based video indexing framework
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
Siwar Baghdadi, Guillaume Gravier, Claire-Hé...