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SCALESPACE
1999
Springer
13 years 12 months ago
A Geometric Functional for Derivatives Approximation
We develop on estimation method, for the derivative field of an image based on Bayesian approach which is formulated in a geometric way. The Maximum probability configuration of ...
Nir A. Sochen, Robert M. Haralick, Yehoshua Y. Zee...
NIPS
2008
13 years 9 months ago
Learning with Consistency between Inductive Functions and Kernels
Regularized Least Squares (RLS) algorithms have the ability to avoid over-fitting problems and to express solutions as kernel expansions. However, we observe that the current RLS ...
Haixuan Yang, Irwin King, Michael R. Lyu
ICIP
2010
IEEE
13 years 5 months ago
Tensor-based image diffusions derived from generalizations of the Total Variation and Beltrami Functionals
We introduce a novel functional for vector-valued images that generalizes several variational methods, such as the Total Variation and Beltrami Functionals. This functional is bas...
Anastasios Roussos, Petros Maragos
ISNN
2007
Springer
14 years 1 months ago
Neural-Based Separating Method for Nonlinear Mixtures
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
Ying Tan
IVC
2008
83views more  IVC 2008»
13 years 7 months ago
A minimum description length objective function for groupwise non-rigid image registration
Groupwise non-rigid registration aims to find a dense correspondence across a set of images, so that analogous structures in the images are aligned. For purely automatic inter-sub...
Stephen Marsland, Carole J. Twining, Christopher J...