DocumentCode
3401356
Title
A neuronet approach to information fusion
Author
Huang, Thomas S. ; Hess, Christopher P. ; Pan, Hao ; Liang, Zhi-Pei
Author_Institution
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
fYear
1997
fDate
23-25 Jun 1997
Firstpage
45
Lastpage
50
Abstract
Neuronet approaches offer a unique and powerful tool for nonlinear information fusion. Unlike traditional techniques, neuronets do not require explicit environmental models or descriptions of sensor characteristics. This paper describes a technique for sensor fusion which makes use of a new neural model to combine data autonomously extracted from different sources. Application of the technique to bimodal recognition of combined speech/image signals is discussed
Keywords
image recognition; neural nets; sensor fusion; speech recognition; bimodal recognition; information fusion; neuronet; nonlinear information fusion; speech/image signals; Artificial neural networks; Biological system modeling; Image recognition; Neural networks; Neurons; Power engineering and energy; Power engineering computing; Sensor fusion; Sensor phenomena and characterization; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Signal Processing, 1997., IEEE First Workshop on
Conference_Location
Princeton, NJ
Print_ISBN
0-7803-3780-8
Type
conf
DOI
10.1109/MMSP.1997.602611
Filename
602611
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