Multimodular Architecture for Remote Sensing Operations.

Part of Advances in Neural Information Processing Systems 4 (NIPS 1991)

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Sylvie Thiria, Carlos Mejia, Fouad Badran, Michel Crépon


This paper deals with an application of Neural Networks to satellite remote sensing observations. Because of the complexity of the application and the large amount of data, the problem cannot be solved by using a single method. The solution we propose is to build multi(cid:173) modules NN architectures where several NN cooperate together. Such system suffer from generic problem for whom we propose solutions. They allow to reach accurate performances for multi-valued function approximations and probability estimations. The results are compared with six other methods which have been used for this problem. We show that the methodology we have developed is general and can be used for a large variety of applications.