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CVPR
2009
IEEE
16 years 11 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...
CVPR
2007
IEEE
16 years 6 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
ICCV
2005
IEEE
16 years 6 months ago
A Generative/Discriminative Learning Algorithm for Image Classification
We have developed a two-phase generative / discriminative learning procedure for the recognition of classes of objects and concepts in outdoor scenes. Our method uses both multipl...
Yi Li, Linda G. Shapiro, Jeff A. Bilmes
ECCV
2008
Springer
16 years 6 months ago
Towards Scalable Dataset Construction: An Active Learning Approach
As computer vision research considers more object categories and greater variation within object categories, it is clear that larger and more exhaustive datasets are necessary. How...
Brendan Collins, Jia Deng, Kai Li, Fei-Fei Li 0002
ECCV
2006
Springer
16 years 6 months ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann