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143
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CVPR
2009
IEEE
16 years 9 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...
133
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...
ECML
2001
Springer
15 years 7 months ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon
174
Voted
ECCV
2010
Springer
15 years 6 months ago
Discriminative Tracking by Metric Learning
We present a discriminative model that casts appearance modeling and visual matching into a single objective for visual tracking. Most previous discriminative models for visual tra...