A review of data fusion models and architectures: Towards engineering guidelines
Date
2005-06-21
Supervisor/s
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Department
Type
Article
ISSN
0941-0643
Format
Free to read from
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.
Description
Software Description
Software Language
Github
Keywords
Data fusion, Frameworks, Intelligent systems, Intelligent systems
DOI
Rights
The final publication is available at Springer via http://dx.doi.org/10.1007/s00521-004-0463-7