Constrained nets for graph matching and other quadratic assignment problems
Neural Computation
Relaxation by the Hopfield neural network
Pattern Recognition
A Bayesian compatibility model for graph matching
Pattern Recognition Letters
A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Algorithm for Error-Tolerant Subgraph Isomorphism Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple graph matching with Bayesian inference
Pattern Recognition Letters - special issue on pattern recognition in practice V
Convergence properties of the softassign quadratic assignment algorithm
Neural Computation
Replicator equations, maximal cliques, and graph isomorphism
Neural Computation
Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics
A Neural Network Approach to CSG-Based 3-D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Matching in Computer Vision Using Probabilistic Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Successive Projection Graph Matching
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Matching Delauny Triangulations by Probabilistic Relaxation
CAIP '95 Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns
A Binary Linear Programming Formulation of the Graph Edit Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
A study of graph spectra for comparing graphs and trees
Pattern Recognition
Attributed relational graph matching based on the nested assignment structure
Pattern Recognition
A quadratic programming based cluster correspondence projection algorithm for fast point matching
Computer Vision and Image Understanding
Reweighted random walks for graph matching
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Computational Optimization and Applications
A sparse nonnegative matrix factorization technique for graph matching problems
Pattern Recognition
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A novel Projections Onto Convex Sets (POCS) graph matching algorithm is presented. Two-way assignment constraints are enforced without using elaborate penalty terms, graduated nonconvexity, or sophisticated annealing mechanisms to escape from poor local minima. Results indicate that the presented algorithm is robust and compares favorably to other well-known algorithms.