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ICICIC
2006
IEEE
15 years 9 months ago
An Edge-Driven Total Variation Approach to Image Deblurring and Denoising
Traditional nonlinear filtering techniques are observed in underutilization of blur identification techniques, and vice versa. To improve blind image restoration, a designed edg...
Hongwei Zheng, Olaf Hellwich
ML
2012
ACM
385views Machine Learning» more  ML 2012»
13 years 10 months ago
An alternative view of variational Bayes and asymptotic approximations of free energy
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Kazuho Watanabe
COLT
2008
Springer
15 years 4 months ago
Extracting Certainty from Uncertainty: Regret Bounded by Variation in Costs
Prediction from expert advice is a fundamental problem in machine learning. A major pillar of the field is the existence of learning algorithms whose average loss approaches that ...
Elad Hazan, Satyen Kale
ICPR
2004
IEEE
16 years 3 months ago
A Variational Approach for Color Image Segmentation
In this paper we use a variational Bayesian framework for color image segmentation. Each image is represented in the L*u*v color coordinate system before being segmented by the va...
Nikolaos Nasios, Adrian G. Bors
SIP
2007
15 years 4 months ago
A variational segmentation framework using active contours and thresholding
Segmentation involves separating distinct regions in an image. In this note, we present a novel variational approach to perform this task. We propose an energy functional that nat...
Samuel Dambreville, Marc Niethammer, Anthony J. Ye...