A review of data fusion models and architectures: Towards engineering guidelines

Date published

2005-06-21

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Springer

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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

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The final publication is available at Springer via http://dx.doi.org/10.1007/s00521-004-0463-7

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