Abstract
Proposes a pattern classification method for remote sensing data based on neural network theory. From Kohonen's self-organizing feature maps, training areas for each pattern are selected. Using the back propagation algorithm, the layered neural network is trained such that the training patterns can be classified within a level. The experiments on LANDSAT TM data show that this approach produces excellent classification results compared with the conventional Bayesian approach. >
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