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» Learning Generic Prior Models for Visual Computation
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CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
ECCV
2002
Springer
15 years 11 months ago
Bayesian Estimation of Layers from Multiple Images
When estimating foreground and background layers (or equivalently an alpha matte), it is often the case that pixel measurements contain mixed colours which are a combination of for...
Yonatan Wexler, Andrew W. Fitzgibbon, Andrew Zisse...
AIED
2009
Springer
15 years 4 months ago
A Phoneme-Based Student Model for Adaptive Spelling Training
We present a novel phoneme-based student model for spelling training. Our model is data driven, adapts to the user and provides information for, e.g., optimal word selection. We de...
Gian-Marco Baschera, Markus Gross
ICIP
2008
IEEE
15 years 11 months ago
Robust snake convergence based on dynamic programming
The extraction of contours using deformable models, such as snakes, is a problem of great interest in computer vision, particular in areas of medical imaging and tracking. Snakes ...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...
CRV
2008
IEEE
205views Robotics» more  CRV 2008»
15 years 4 months ago
Accurate Boundary Localization using Dynamic Programming on Snakes
The extraction of contours using deformable models, such as snakes, is a problem of great interest in computer vision, particular in areas of medical imaging and tracking. Snakes ...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...