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NECO
2008
108views more  NECO 2008»
15 years 4 months ago
Optimal Approximation of Signal Priors
In signal restoration by Bayesian inference, one typically uses a parametric model of the prior distribution of the signal. Here, we consider how the parameters of a prior model s...
Aapo Hyvärinen
PAMI
2008
391views more  PAMI 2008»
15 years 4 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha
NN
2006
Springer
153views Neural Networks» more  NN 2006»
15 years 4 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
PAMI
2006
122views more  PAMI 2006»
15 years 4 months ago
Total Variation Models for Variable Lighting Face Recognition
In this paper, we present the logarithmic total variation (LTV) model for face recognition under varying illumination, including natural lighting conditions, where we rarely know t...
Terrence Chen, Wotao Yin, Xiang Sean Zhou, Dorin C...
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PAMI
2006
202views more  PAMI 2006»
15 years 4 months ago
Pose and Motion Recovery from Feature Correspondences and a Digital Terrain Map
A novel algorithm for pose and motion estimation using corresponding features and a Digital Terrain Map is proposed. Using a Digital Terrain (or Digital Elevation) Map (DTM/DEM) as...
Ronen Lerner, Ehud Rivlin, Héctor Rotstein