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» Robust feature extraction via information theoretic learning
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ICRA
2005
IEEE
138views Robotics» more  ICRA 2005»
15 years 5 months ago
Urban Object Recognition from Informative Local Features
Abstract— Autonomous mobile agents require object recognition for high level interpretation and localization in complex scenes. In urban environments, recognition of buildings mi...
Gerald Fritz, Christin Seifert, Lucas Paletta
ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
15 years 6 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
CVPR
2008
IEEE
16 years 1 months ago
On the use of independent tasks for face recognition
We present a method for learning discriminative linear feature extraction using independent tasks. More concretely, given a target classification task, we consider a complementary...
Àgata Lapedriza, David Masip, Jordi Vitri&a...
ICML
2004
IEEE
16 years 14 days ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
ICCV
2011
IEEE
13 years 11 months ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus