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BMVC
2010
14 years 10 months ago
Diffusion-based Regularisation Strategies for Variational Level Set Segmentation
Variational level set methods are formulated as energy minimisation problems, which are often solved by gradient-based optimisation methods, such as gradient descent. Unfortunatel...
Maximilian Baust, Darko Zikic, Nassir Navab
JMLR
2010
136views more  JMLR 2010»
14 years 7 months ago
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential family using the variational Bayesian expectation maximisation (VB EM) algorith...
Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti...
CVPR
2007
IEEE
16 years 2 months ago
A Variational Approach to the Evolution of Radial Basis Functions for Image Segmentation
In this paper we derive differential equations for evolving radial basis functions (RBFs) to solve segmentation problems. The differential equations result from applying variation...
Greg G. Slabaugh, Huong Quynh Dinh, Gozde B. Unal
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CVPR
2007
IEEE
16 years 2 months ago
Variational Bayes Based Approach to Robust Subspace Learning
This paper presents a new algorithm for the problem of robust subspace learning (RSL), i.e., the estimation of linear subspace parameters from a set of data points in the presence...
Takayuki Okatani, Koichiro Deguchi
ICIP
2007
IEEE
16 years 2 months ago
A Variational Approach to Exploit Prior Information in Object-Background Segregation: Application to Retinal Images
One of the main challenges in image segmentation is to adapt prior knowledge about the objects/regions that are likely to be present in an image, in order to obtain more precise d...
Luca Bertelli, Jiyun Byun, B. S. Manjunath