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Satellite image analysis using neural networksThe tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.
Document ID
19900013005
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Sheldon, Roger A.
(Ford Aerospace Corp. Seabrook, MD, United States)
Date Acquired
September 6, 2013
Publication Date
May 1, 1990
Publication Information
Publication: NASA, Goddard Space Flight Center, The 1990 Goddard Conference on Space Applications of Artificial Intelligence
Subject Category
Cybernetics
Accession Number
90N22321
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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