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ESOP
2011
Springer
14 years 3 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
CGF
2008
98views more  CGF 2008»
14 years 12 months ago
Texture Synthesis From Photographs
The goal of texture synthesis is to generate an arbitrarily large high-quality texture from a small input sample. Generally, it is assumed that the input image is given as a flat,...
Christian Eisenacher, Sylvain Lefebvre, Marc Stamm...
CVPR
2010
IEEE
15 years 5 months ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia
MM
2009
ACM
277views Multimedia» more  MM 2009»
15 years 6 months ago
Inferring semantic concepts from community-contributed images and noisy tags
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun ...
AUTOMATICA
2004
91views more  AUTOMATICA 2004»
14 years 11 months ago
Comparing digital implementation via the bilinear and step-invariant transformations
From an analog system K, digital systems Kd and Kbt are often obtained via the step-invariant and bilinear transformations, respectively. For the case when K is stable, it is show...
Guofeng Zhang, Tongwen Chen