D-CIS Publication Database

Publication

Type of publication:Inproceedings
Entered by:MvI
Title
Bibtex cite ID
Booktitle International Conference on Multisensor Fusion and Integration for Intelligent Systems
Year published 2006
Location Heidelberg, Germany
Keywords distributed fusion,Bayesian networks
Abstract
We introduce Distributed perception networks (DPNs), a distributed architecture for efficient and reliable fusion of large quantities of heterogeneous and noisy information. DPNs consist of agents, processing nodes with limited fusion capabilities, which cooperate and can autonomously form arbitrarily large distributed classifiers. DPNs are based on causal models, which often facilitate analysis, design and maintenance of complex information fusion systems. This is possible because observations obtained from different information sources often result from causal processes which in turn can be modeled with relatively simple, yet mathematically rigorous and compact probabilistic causal models. Such models, in turn, facilitate decentralized world modeling and information fusion.
Authors
Pavlin, Gregor
de Oude, Patrick
Maris, Marinus
Hood, Thomas
Topics
=SEE CLASSIFICATION DIFFERENCE FROM OTHERS=
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Attachments
MFI-final-GP-0607.pdf (main file)
 
Total mark: 5