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Effective and understanding exploration of hyperspectral remote sensing data necessitates the development of sophisticated schemes that represent images. Such schemes ideally preserve and recognize si...
In this paper, series of experimental studies about the neural network model for whiskbroom remote sensing imagery geometry correction methods based on BPNN (Back-Propagation Neural Networks) and RBFN...
In the last twenty-five years a great number of vectorization methods were developed. In this paper we first give an overview about the most known methods, and then propose a vectorization algorithm b...
For global data representation, like the approximation of a surface, algebraic or trigonometric polynomials may be used. However, polynomial approaches are limited concerning their accuracy. In the la...
In this paper we report the results of an experimental analysis on the use of two neural models for the thematic classification of multispectral remotely sensed data. A Back Propagation network with ...
DISCRIMINATION ABILITY OF NEURAL NETWORK AND MAXIMUM LIKELIHOOD CLASSIFIERS.
The artificial neural networks are nice tools in the thematic mapping. The classification procedure requires carefully prepared training set. The research was aimed to show the effect of the generally...

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