Neural Networks for Perception: Computation, Learning, and Architecture

This comprehensive volume explores recent research in neural networks that has advanced our understanding of human and machine perception. Contributions from leading international researchers address both theoretical and practical issues related to the feasibility of neural network models to explain human perception and implement machine perception. The book covers models for understanding human perception in terms of distributed computation as well as examples of neural network models for machine perception.