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TSP
2008
105views more  TSP 2008»
13 years 9 months ago
Semi-Supervised Linear Spectral Unmixing Using a Hierarchical Bayesian Model for Hyperspectral Imagery
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linea...
Nicolas Dobigeon, Jean-Yves Tourneret, Chein-I Cha...
ICASSP
2010
IEEE
13 years 8 months ago
A hierarchical Bayesian model for frame representation
In many signal processing problems, it may be fruitful to represent the signal under study in a redundant linear decomposition called a frame. If a probabilistic approach is adopt...
Lotfi Chaâri, Jean-Christophe Pesquet, Jean-...
CSDA
2007
105views more  CSDA 2007»
13 years 9 months ago
Joint segmentation of wind speed and direction using a hierarchical model
The problem of detecting changes in wind speed and direction is considered. Bayesian priors, with various degrees of certainty, are used to represent relationships between the two...
Nicolas Dobigeon, Jean-Yves Tourneret
NIPS
1997
13 years 11 months ago
Graph Matching with Hierarchical Discrete Relaxation
Our aim in this paper is to develop a Bayesian framework for matching hierarchical relational models. Such models are widespread in computer vision. The framework that we adopt fo...
Richard C. Wilson, Edwin R. Hancock
ALGORITHMICA
2006
132views more  ALGORITHMICA 2006»
13 years 9 months ago
Straight-Line Drawing Algorithms for Hierarchical Graphs and Clustered Graphs
Hierarchical graphs and clustered graphs are useful non-classical graph models for structured relational information. Hierarchical graphs are graphs with layering structures; clus...
Peter Eades, Qing-Wen Feng, Xuemin Lin, Hiroshi Na...