Sciweavers

196 search results - page 5 / 40
» Unsupervised image embedding using nonparametric statistics
Sort
View
ICIP
2002
IEEE
14 years 10 months ago
Nonparametric methods for image segmentation using information theory and curve evolution
In this paper, we present a novel information theoretic approach to image segmentation. We cast the segmentation problem as the maximization of the mutual information between the ...
Alan S. Willsky, Anthony J. Yezzi Jr., John W. Fis...
ICIP
2005
IEEE
14 years 10 months ago
Feature selection with nonparametric statistics
In this paper we discuss a general framework for feature selection based on nonparametric statistics. The three stage approach we propose is based on the assumption that the avail...
Emanuele Franceschi, Francesca Odone, Fabrizio Sme...
ICIP
2006
IEEE
14 years 10 months ago
Using Non-Parametric Kernel to Segment and Smooth Images Simultaneously
Piecewise constant and piecewise smooth Mumford-Shah (MS) models have been widely studied and used for image segmentation. More complicated than piecewise constant MS, global Gaus...
Weihong Guo, Yunmei Chen
ECML
2007
Springer
14 years 2 months ago
Spectral Clustering and Embedding with Hidden Markov Models
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Tony Jebara, Yingbo Song, Kapil Thadani
ICIP
2003
IEEE
14 years 10 months ago
Incorporating complex statistical information in active contour-based image segmentation
We propose an information-theoretic method for multi-phase image segmentation, in an active contour-based framework. Our approach is based on nonparametric density estimates, and ...
Alan S. Willsky, Anthony J. Yezzi, John W. Fisher ...