A massively parallel architecture for a self-organizing neural pattern recognition machine
Computer Vision, Graphics, and Image Processing
Schemas and neural networks for sixth generation computing. Invited survey
Journal of Parallel and Distributed Computing - Neural Computing
Multilayer feedforward networks are universal approximators
Neural Networks
Boundary Detection by Constrained Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Review of neural networks for speech recognition
Neural Computation
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Pattern recognition: statistical, structural and neural approaches
Pattern recognition: statistical, structural and neural approaches
Neural networks and the bias/variance dilemma
Neural Computation
The Metaphorical Brain 2: Neural Networks and Beyond
The Metaphorical Brain 2: Neural Networks and Beyond
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Image segmentation based on oscillatory correlation
Neural Computation
A Path Finding Via VRML and VISION Overlay for Autonomous Robot
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Expert Systems with Applications: An International Journal
An individual adaptive gain parameter backpropagation algorithm for complex-valued neural networks
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
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Invariant pattern recognition will be a problem facing neural networks for some time, and the challenge is to overcome the limitation of Hamming distance generalization. Four representative architectures that are able to generalize are reviewed. The architectures are the backpropagation network, the ART architecture, the dynamic link architecture, and associate memories. Image representation, segmentation, and invariance are discussed.