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» Nonparametric prior for adaptive sparsity
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VLSM
2005
Springer
15 years 3 months ago
Uncertainty-Driven Non-parametric Knowledge-Based Segmentation: The Corpus Callosum Case
Abstract. In this paper we propose a novel variational technique for the knowledge based segmentation of two dimensional objects. One of the elements of our approach is the use of ...
Maxime Taron, Nikos Paragios, Marie-Pierre Jolly
ECAI
2010
Springer
14 years 10 months ago
Kernel Methods for Revealed Preference Analysis
In classical revealed preference analysis we are given a sequence of linear prices (i.e., additive over goods) and an agent's demand at each of the prices. The problem is to d...
Sébastien Lahaie
SCALESPACE
2007
Springer
15 years 3 months ago
Best Basis Compressed Sensing
This paper proposes an extension of compressed sensing that allows to express the sparsity prior in a dictionary of bases. This enables the use of the random sampling strategy of c...
Gabriel Peyré
TIP
2008
213views more  TIP 2008»
14 years 8 months ago
Deblurring Using Regularized Locally Adaptive Kernel Regression
Kernel regression is an effective tool for a variety of image processing tasks such as denoising and interpolation [1]. In this paper, we extend the use of kernel regression for de...
Hiroyuki Takeda, Sina Farsiu, Peyman Milanfar
SIAMIS
2010
156views more  SIAMIS 2010»
14 years 4 months ago
Learning the Morphological Diversity
This article proposes a new method for image separation into a linear combination of morphological components. Sparsity in fixed dictionaries is used to extract the cartoon and osc...
Gabriel Peyré, Jalal Fadili, Jean-Luc Starc...