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» Automatic feature localisation with constrained local models
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ICCV
2003
IEEE
14 years 9 months ago
Ranking Prior Likelihood Distributions for Bayesian Shape Localization Framework
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
Shuicheng Yan, Mingjing Li, HongJiang Zhang, QianS...
AIED
2007
Springer
14 years 1 months ago
Comparing Linguistic Features for Modeling Learning in Computer Tutoring
We compare the relative utility of different automatically computable linguistic feature sets for modeling student learning in computer dialogue tutoring. We use the PARADISE frame...
Katherine Forbes-Riley, Diane J. Litman, Amruta Pu...
TIP
1998
99views more  TIP 1998»
13 years 7 months ago
Nonlinear image estimation using piecewise and local image models
—We introduce a new approach to image estimation based on a flexible constraint framework that encapsulates meaningful structural image assumptions. Piecewise image models (PIM...
Scott T. Acton, Alan C. Bovik
CVPR
2012
IEEE
11 years 10 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann
AOSD
2008
ACM
13 years 9 months ago
Modularity first: a case for mixing AOP and attribute grammars
We have reimplemented the frontend of the extensible AspectBench Compiler for AspectJ, using the aspect-oriented meta-compiler JastAdd. The original frontend was purely object-ori...
Pavel Avgustinov, Torbjörn Ekman, Julian Tibb...