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AUSAI
2005
Springer
16 years 5 hour ago
Resampling LDA/QR and PCA+LDA for Face Recognition
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...
Jun Liu, Songcan Chen
JMLR
2010
192views more  JMLR 2010»
15 years 1 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
ICDAR
2011
IEEE
14 years 6 months ago
Three Dimensional Rotation-Free Recognition of Characters
—In this paper, we propose a new method for three dimensional rotation-free recognition of characters in scene. In the proposed method, we employ the Modified Quadratic Discrimi...
Ryo Narita, Wataru Ohyama, Tetsushi Wakabayashi, F...
ICASSP
2010
IEEE
15 years 6 months ago
Visual localization and segmentation based on foreground/background modeling
In this paper, we propose a novel method to localize (or track) a foreground object and segment the foreground object from the surrounding background with occlusions for a moving ...
Hanzi Wang, Tat-Jun Chin, David Suter
ICPR
2008
IEEE
16 years 27 days ago
Model-based visual self-localization using geometry and graphs
In this paper, a geometric approach for global selflocalization based on a world-model and active stereo vision is introduced. The method uses class specific object recognition a...
David Israel Gonzalez-Aguirre, Tamim Asfour, Eduar...