IEEE Transactions on Systems, Man and Cybernetics
Automated visual inspection: 1981 to 1987
Computer Vision, Graphics, and Image Processing
Schemas and neural networks for sixth generation computing. Invited survey
Journal of Parallel and Distributed Computing - Neural Computing
A unified systolic architecture for artificial neural networks
Journal of Parallel and Distributed Computing - Neural Computing
Cognizers, neural networks, and machines that think
Cognizers, neural networks, and machines that think
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Engineering Intelligent Systems: Concepts, Theory, and Applications
Engineering Intelligent Systems: Concepts, Theory, and Applications
Information Theory and Reliable Communication
Information Theory and Reliable Communication
Perceptrons: An Introduction to Computational Geometry
Perceptrons: An Introduction to Computational Geometry
Shape quantization and recognition with randomized trees
Neural Computation
Vision Experiments with Neural Deformable Template Matching
Neural Processing Letters
A Boolean Neural Network Approach for the Traveling Salesman Problem
IEEE Transactions on Computers
Design of Supervised Classifiers Using Boolean Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Attractor Networks for Shape Recognition
Neural Computation
Benchmarking: an interactive tool for vectorization of raster images
SENSIG'09/VIS'09/MATERIALS'09 Proceedings of the 2nd WSEAS International Conference on Sensors, and Signals and Visualization, Imaging and Simulation and Materials Science
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Presents a feature recognition network for pattern recognition that learns the patterns by remembering their different segments. The base algorithm for this network is a Boolean net algorithm that the authors developed during past research. Simulation results show that the network can recognize patterns after significant noise, deformation, translation and even scaling. The network is compared to existing popular networks used for the same purpose, especially the Neocognitron. The network is also analyzed as regards to interconnection complexity and information storage/retrieval.