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ICCV
2003
IEEE
14 years 9 months ago
A Bayesian Network Framework for Relational Shape Matching
A Bayesian network formulation for relational shape matching is presented. The main advantage of the relational shape matching approach is the obviation of the non-rigid spatial m...
Anand Rangarajan, James M. Coughlan, Alan L. Yuill...
VLUDS
2010
270views Visualization» more  VLUDS 2010»
13 years 2 months ago
Detection and Identification Techniques for Markers Used in Computer Vision
This paper summarizes and compares techniques for detecting and identifying markers in the context of computer vision. Existing approaches use correlation, digital, or topological...
Johannes Köhler, Alain Pagani, Didier Stricke...
MCS
2005
Springer
14 years 1 months ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
BMCBI
2006
138views more  BMCBI 2006»
13 years 7 months ago
Determination of strongly overlapping signaling activity from microarray data
Background: As numerous diseases involve errors in signal transduction, modern therapeutics often target proteins involved in cellular signaling. Interpretation of the activity of...
Ghislain Bidaut, Karsten Suhre, Jean-Michel Claver...
ECML
2001
Springer
14 years 2 days ago
Learning of Variability for Invariant Statistical Pattern Recognition
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...
Daniel Keysers, Wolfgang Macherey, Jörg Dahme...