A review of data fusion models and architectures: Towards engineering guidelines
| dc.contributor.author | Esteban, Jaime | |
| dc.contributor.author | Starr, Andrew G. | |
| dc.contributor.author | Willetts, Robert | |
| dc.contributor.author | Hannah, Paul | |
| dc.contributor.author | Bryanston-Cross, Peter | |
| dc.date.accessioned | 2016-04-18T15:13:54Z | |
| dc.date.available | 2016-04-18T15:13:54Z | |
| dc.date.issued | 2005-06-21 | |
| dc.description.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. | en_UK |
| dc.identifier.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 | en_UK |
| dc.identifier.issn | 0941-0643 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/9826 | |
| dc.identifier.uri | http://dx.doi.org/10.1007/s00521-004-0463-7 | en_UK |
| dc.language.iso | en | en_UK |
| dc.publisher | Springer | en_UK |
| dc.rights | The final publication is available at Springer via http://dx.doi.org/10.1007/s00521-004-0463-7 | en_UK |
| dc.subject | Data fusion | en_UK |
| dc.subject | Frameworks | en_UK |
| dc.subject | Intelligent systems | en_UK |
| dc.subject | Intelligent systems | en_UK |
| dc.title | A review of data fusion models and architectures: Towards engineering guidelines | en_UK |
| dc.type | Article | en_UK |