Title :
Literature review of artificial neural networks and knowledge-based systems for image analysis and interpretation of data in remote sensing
Author :
Goita, Kalifa ; Gonzalez-Rubio, R. ; Benie, G.B. ; Royer, Alain ; Michaud, Francois
Author_Institution :
Centre d´Applications et de Recherches en Teledetection, Sherbrooke Univ., Que., Canada
fDate :
4/1/1994 12:00:00 AM
Abstract :
Remote sensing is a scientific discipline involved in the study and management of the environment and natural resources. Current developments in data acquisition and the diversity of sensors generate great amounts of data. The analysis and interpretation of these data requires sophisticated techniques. Some of these techniques come from the artificial intelligence field, and are being used more and more. This article provides a synthesis of how knowledge systems and artificial neural nets are applied in the analysis and interpretation of data coming from remote sensing. The concepts of these two systems are briefly presented and some examples are presented of how they are used or could be used in remote sensing.
Keywords :
data acquisition; image processing; knowledge based systems; neural nets; remote sensing; reviews; artificial intelligence; artificial neural nets; artificial neural networks; data acquisition; data analysis; environment management; image analysis; image interpretation; knowledge systems; knowledge-based systems; literature review; natural resources management; remote sensing data; sensors; Earth; Gold; Image segmentation; RNA; Remote sensing; Satellites; Silicon;
Journal_Title :
Electrical and Computer Engineering, Canadian Journal of
DOI :
10.1109/CJECE.1994.6592069