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
Link To Document :
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