A controversial issue in the research of mathematics of intelligence has been that of the roles of a priori knowledge versus adaptive learning. After discussing mathematical difficulties of combining a priority with adaptivity encountered in the past, we introduce a concept of a model-based neural network, whose adaptive learning is based on a priori models. Applications to target detection in SAR images are discussed. We briefly overview the SAR principles, derive relatively simple physics-based models of SAR signals, and describe model-based neural networks that utilize these models. A number of real-world application examples are presented. © 1997 IEEE.
CITATION STYLE
Perlovsky, L. I., Schoendorf, W. H., Burdick, B. J., & Tye, D. M. (1997). Model-based neural network for target detection in SAR images. IEEE Transactions on Image Processing, 6(1), 203–216. https://doi.org/10.1109/83.552107
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