An Image Understanding System Using Attributed Symbolic Representation and Inexact Graph-Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Relaxation by the Hopfield neural network
Pattern Recognition
A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shock Graphs and Shape Matching
International Journal of Computer Vision
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Comparing Structures Using a Hopfield-Style Neural Network
Applied Intelligence
Structural Matching in Computer Vision Using Probabilistic Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-organizing map for clustering in the graph domain
Pattern Recognition Letters - In memory of Professor E.S. Gelsema
Fast Winner-Takes-All Networks for the Maximum Clique Problem
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
A novel optimizing network architecture with applications
Neural Computation
A versatile computer-controlled assembly system
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
A novel neural network approach to solve exact and inexact graph isomorphism problems
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Supervised neural networks for the classification of structures
IEEE Transactions on Neural Networks
Approximating maximum clique with a Hopfield network
IEEE Transactions on Neural Networks
Central Clustering of Attributed Graphs
Machine Learning
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We propose a winner-takes-all (WTA) classifier for structures represented by graphs. WTA classification follows the principle elimination of competition. The input structure is assigned to the class corresponding to the winner of the competition. In experiments we investigate the performance of the WTA classifier and compare it with the canonical maximum similarity (MS) classifier.