DocumentCode
3064684
Title
Multi-sensor data fusion using neural networks
Author
Fincher, D. Wade ; Mix, Dwight F.
Author_Institution
Dept. of Electr. Eng., Arkansas Univ., Fayetteville, AR, USA
fYear
1990
fDate
4-7 Nov 1990
Firstpage
835
Lastpage
838
Abstract
A general approach to the use of neural networks for data fusion is outlined. The discussion begins with examples of data fusion problems and a pattern recognition example is given to illustrate the concepts involved in data fusion. The differences between using post- and pre-detection signals and the advantages of using the latter are discussed. How to apply a neural network to the data fusion problem is demonstrated, and experimental results for a character recognition task are given. The general approach applies to a variety of practical situations, including robot navigation and military environment assessment/evaluation
Keywords
character recognition; computer vision; neural nets; pattern recognition; character recognition; computer vision; multisensor data fusion; neural networks; pattern recognition; Bayesian methods; Character recognition; Cost function; Modems; Neural networks; Pattern recognition; Robot sensing systems; Sensor fusion; Sensor phenomena and characterization; Sensor systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on
Conference_Location
Los Angeles, CA
Print_ISBN
0-87942-597-0
Type
conf
DOI
10.1109/ICSMC.1990.142240
Filename
142240
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