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TNN
2008
177views more  TNN 2008»
13 years 7 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal
ICPR
2006
IEEE
14 years 8 months ago
Adaptive variational sinogram interpolation of sparsely sampled CT data
We present various kinds of variational PDE based methods to interpolate missing sinogram data for tomographic image reconstruction. Using the observed sinogram data we inpaint th...
Harald Köstler, Marcus Prümmer, Ulrich R...
CVPR
2009
IEEE
15 years 6 days ago
Tracking of a Non-Rigid Object via Patch-based Dynamic Appearance Modeling and Adaptive Basin Hopping Monte Carlo Sampling
We propose a novel tracking algorithm for the target of which geometric appearance changes drastically over time. To track it, we present a local patch-based appearance model and p...
Junseok Kwon (Seoul National University), Kyoung M...
FGR
2011
IEEE
272views Biometrics» more  FGR 2011»
12 years 11 months ago
Adaptive discriminant analysis for face recognition from single sample per person
—Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition...
Meina Kan, Shiguang Shan, Yu Su, Xilin Chen, Wen G...
TOG
2010
134views more  TOG 2010»
13 years 2 months ago
Unbiased, adaptive stochastic sampling for rendering inhomogeneous participating media
Realistic rendering of participating media is one of the major subjects in computer graphics. Monte Carlo techniques are widely used for realistic rendering because they provide u...
Yonghao Yue, Kei Iwasaki, Bing-Yu Chen, Yoshinori ...