NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Real-time expert system and neural network for the classification of remotely sensed dataThe paper examines software techniques for classifying remotely sensed data such that the number of computational steps and the amount of resources are bounded. The combination of both neural network and expert system methodology for classifying these data based on land use/land cover categories is examined. The method involves pipelining images through a neural net for initial classification and then through the expert system which resolves the ambiguous classifications. As with any pipeline, every component must have approximately equivalent run-times or otherwise a bottleneck will occur. If real-time is a requirement, each of the components must execute within a bounded number of steps. Attention is focused on the real-time system technique, which is argued to prevent a bottleneck for this data classification application.
Document ID
19920056770
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Short, Nicholas, Jr.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 15, 2013
Publication Date
January 1, 1991
Subject Category
Cybernetics
Meeting Information
Meeting: 1991 ACSM-ASPRS Annual Convention
Location: Baltimore, MD
Country: United States
Start Date: March 25, 1991
End Date: March 29, 1991
Accession Number
92A39394
Distribution Limits
Public
Copyright
Other

Available Downloads

There are no available downloads for this record.
No Preview Available