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» Rigorous Result for the CHKNS Random Graph Model
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ICML
2007
IEEE
14 years 9 months ago
Parameter learning for relational Bayesian networks
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Manfred Jaeger
ICIP
2008
IEEE
14 years 2 months ago
MAP-MRF approach for binarization of degraded document image
We propose an algorithm for the binarization of document images degraded by uneven light distribution, based on the Markov Random Field modeling with Maximum A Posteriori probabil...
Jung Gap Kuk, Nam Ik Cho, Kyoung Mu Lee
SAC
2010
ACM
14 years 3 months ago
Estimating node similarity from co-citation in a spatial graph model
Co-citation (number of nodes linking to both of a given pair of nodes) is often used heuristically to judge similarity between nodes in a complex network. We investigate the relat...
Jeannette Janssen, Pawel Pralat, Rory Wilson
MICCAI
2010
Springer
13 years 7 months ago
Non-parametric Iterative Model Constraint Graph min-cut for Automatic Kidney Segmentation
We present a new non-parametric model constraint graph min-cut algorithm for automatic kidney segmentation in CT images. The segmentation is formulated as a maximum a-posteriori es...
Moti Freiman, A. Kronman, S. J. Esses, Leo Joskowi...
MIR
2006
ACM
223views Multimedia» more  MIR 2006»
14 years 2 months ago
Adaptive image retrieval using a Graph model for semantic feature integration
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
Jana Urban, Joemon M. Jose