Multisensor image classification by structured neural networks

The application of structured neural networks to the supervised classification of multisensor images is discussed. The purpose is to give a criterion for network architecture definition and to allow the interpretation of the network behavior. The latter result can be used to understand the importance of sensors and related channels to the classification task. The networks' architecture is configured by exploiting the characteristics of a given multisensor classification problem. Then, such networks are trained to solve the problem. Finally, they are transformed into equivalent networks to obtain a simplified representation.<
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