A review of data fusion models and architectures: Towards engineering guidelines
Date published
2005-06-21
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Journal Title
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Volume Title
Publisher
Springer
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Type
Article
ISSN
0941-0643
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Citation
Esteban, J. Starr, A. Willetts, R. Hannah, P. Bryanston-Cross, P. A review of data fusion models and architectures: Towards engineering guidelines. Neural Computing & Applications. December 2005, Volume 14, Issue 4, pp 273-281
Abstract
This paper reviews the potential benefits that can be obtained by the implementation of data fusion in a multi-sensor environment. A thorough review of the commonly used data fusion frameworks is presented together with important factors that need to be considered during the development of an effective data fusion problem-solving strategy. A system-based approach is defined for the application of data fusion systems within engineering. Structured guidelines for users are proposed.
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Github
Keywords
Data fusion, Frameworks, Intelligent systems, Intelligent systems
DOI
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The final publication is available at Springer via http://dx.doi.org/10.1007/s00521-004-0463-7