Application of neural networks to terrain classification

Results of an investigation into the applicability of neural networks to the classification of radar terrain images are reported. The neural network approach is described and compared with the conventional technique of Bayesian classification with maximum-likelihood estimation. Performance that was previously thought to be optimal is shown to be improved upon by the use of neural networks. The results shown generalize to all applications currently employing Bayesian classification.>