Title :
Neural net architectures for scope check and monitoring
Author :
Schiller, Helmut
Author_Institution :
GKSS Forschungszentrum, Geesthacht, Germany
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;
Conference_Titel :
Computational Intelligence for Measurement Systems and Applications, 2003. CIMSA '03. 2003 IEEE International Symposium on
Print_ISBN :
0-7803-7783-4
DOI :
10.1109/CIMSA.2003.1227206
