DocumentCode
1984406
Title
Neural net architectures for scope check and monitoring
Author
Schiller, Helmut
Author_Institution
GKSS Forschungszentrum, Geesthacht, Germany
fYear
2003
fDate
29-31 July 2003
Firstpage
79
Lastpage
84
Abstract
The application of two kinds of autoassociative NN´s is discussed. The applications concern observation of the marine environment. The first kind of autoassociative NN has physical interpretable neurons in the bottleneck layer and is used for scope check in the retrieval of concentrations of water constituents. The second kind is a standard autoassociative NN which we propose to use in the monitoring of the environment. An example of such a usage is given.
Keywords
feedforward neural nets; generalisation (artificial intelligence); geophysics computing; monitoring; neural net architecture; remote sensing; autoassociative neural net; concentrations; marine environment; monitoring; neural net architecture; physical interpretable neurons; scope check; water constituents; Atmospheric measurements; Cameras; Earth; Geophysical measurements; MERIS; Monitoring; Neural networks; Oceans; Satellites; Sea measurements;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Measurement Systems and Applications, 2003. CIMSA '03. 2003 IEEE International Symposium on
Print_ISBN
0-7803-7783-4
Type
conf
DOI
10.1109/CIMSA.2003.1227206
Filename
1227206
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