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Proceedings Paper

Information extraction from the GER 63-channel spectrometer data
Author(s): Richard K. Kiang
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Paper Abstract

The unprecedented data volume in the era of NASA's Mission to Planet Earth (MTPE) demands innovative information extraction methods and advanced processing techniques. The neural network techniques, which are intrinsic to distributed parallel processings and have shown promising results in analyzing remotely sensed data, could become the essential tools in the MTPE era. To evaluate the information content of data with higher dimension and the usefulness of neural networks in analyzing them, measurements from the GER 63-channel airborne imaging spectrometer data over Cuprite, Nevada, are used. The data are classified with 3-layer Perceptron of various architectures. It is shown that the neural network can achieve a level of performance similar to conventional methods, without the need for an explicit feature extraction step.

Paper Details

Date Published: 23 September 1993
PDF: 7 pages
Proc. SPIE 1937, Imaging Spectrometry of the Terrestrial Environment, (23 September 1993); doi: 10.1117/12.157048
Show Author Affiliations
Richard K. Kiang, NASA Goddard Space Flight Ctr. (United States)

Published in SPIE Proceedings Vol. 1937:
Imaging Spectrometry of the Terrestrial Environment
Gregg Vane, Editor(s)

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