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ICIP
2003
IEEE
16 years 5 months ago
Adaptive principal components and image denoising
This paper presents a novel approach to image denoising using adaptive principal components. Our assumptions are that the image is corrupted by additive white Gaussian noise. The ...
D. Darian Muresan, Thomas W. Parks
ICAISC
2004
Springer
15 years 9 months ago
Visualizing and Analyzing Multidimensional Output from MLP Networks via Barycentric Projections
Barycentric plotting, achieved by placing gaussian kernels in distant corners of the feature space and projecting multidimensional output of neural network on a plane, provides inf...
Filip Piekniewski, Leszek Rybicki
NIPS
2001
15 years 5 months ago
A Variational Approach to Learning Curves
We combine the replica approach from statistical physics with a variational approach to analyze learning curves analytically. We apply the method to Gaussian process regression. A...
Dörthe Malzahn, Manfred Opper
ICPR
2008
IEEE
15 years 10 months ago
Combining shape-from-shading and stereo using Gaussian-Markov random fields
In this paper we present a method of combining stereo and shape-from-shading information, taking account of the local reliability of each shape estimate. Local estimates of dispar...
Tom S. F. Haines, Richard C. Wilson
ICIP
2007
IEEE
16 years 6 months ago
Robust Image Segmentation with Mixtures of Student's t-Distributions
Gaussian mixture models have been widely used in image segmentation. However, such models are sensitive to outliers. In this paper, we consider a robust model for image segmentati...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...