A Bayesian compatibility model for graph matching
Pattern Recognition Letters
A Bayesian interpretation for the exponential correlation associative memory
Pattern Recognition Letters
Pattern Recognition Letters - Special issue: In memoriam Azriel Rosenfeld
Efficient MAP approximation for dense energy functions
ICML '06 Proceedings of the 23rd international conference on Machine learning
Fuzzy Cognitive Maps for stereovision matching
Pattern Recognition
Retrieval of objects in video by similarity based on graph matching
Pattern Recognition Letters
Iterated tensor voting and curvature improvement
Signal Processing
Probabilistic relaxation labelling using the Fokker-Planck equation
Pattern Recognition
Robust feature point matching by preserving local geometric consistency
Computer Vision and Image Understanding
An adaptive ontology mapping approach with neural network based constraint satisfaction
Web Semantics: Science, Services and Agents on the World Wide Web
An expert system for detecting automobile insurance fraud using social network analysis
Expert Systems with Applications: An International Journal
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Image and Vision Computing
A robust hybrid method for nonrigid image registration
Pattern Recognition
Measuring 3D shape similarity by graph-based matching of the medial scaffolds
Computer Vision and Image Understanding
A new graph matching method for point-set correspondence using the EM algorithm and Softassign
Computer Vision and Image Understanding
Batch Mode Active Learning for Networked Data
ACM Transactions on Intelligent Systems and Technology (TIST)
A graph spectral approach to consistent labelling
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Defining consistency to detect change using inexact graph matching
GbRPR'05 Proceedings of the 5th IAPR international conference on Graph-Based Representations in Pattern Recognition
Graph transduction as a noncooperative game
Neural Computation
Relevance criteria for data mining using error-tolerant graph matching
IWCIA'06 Proceedings of the 11th international conference on Combinatorial Image Analysis
Color image segmentation for Bladder Cancer Diagnosis
Mathematical and Computer Modelling: An International Journal
Restoration of binary images using stochastic relaxation with annealing
Pattern Recognition Letters
Copositive-plus Lemke algorithm solves polymatrix games
Operations Research Letters
A constraint-based hypergraph partitioning approach to coreference resolution
Computational Linguistics
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A large class of problems can be formulated in terms of the assignment of labels to objects. Frequently, processes are needed which reduce ambiguity and noise, and select the best label among several possible choices. Relaxation labeling processes are just such a class of algorithms. They are based on the parallel use of local constraints between labels. This paper develops a theory to characterize the goal of relaxation labeling. The theory is founded on a definition of con-sistency in labelings, extending the notion of constraint satisfaction. In certain restricted circumstances, an explicit functional exists that can be maximized to guide the search for consistent labelings. This functional is used to derive a new relaxation labeling operator. When the restrictions are not satisfied, the theory relies on variational cal-culus. It is shown that the problem of finding consistent labelings is equivalent to solving a variational inequality. A procedure nearly identical to the relaxation operator derived under restricted circum-stances serves in the more general setting. Further, a local convergence result is established for this operator. The standard relaxation labeling formulas are shown to approximate our new operator, which leads us to conjecture that successful applications of the standard methods are explainable by the theory developed here. Observations about con-vergence and generalizations to higher order compatibility relations are described.