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Application of Two-Level Joint Information Fusion Model in Intelligent Vehicle
2016
International Journal of Online Engineering (iJOE)
This paper proposes a two-level joint information fusion model combining BP neural network and D-S evidence theory. The model of great practical value reduces target identification error probability by multiple features of the target information, shows good scalability with its two steps of information fusion model, and conveniently increases/reduces feature fusion information source according to different situations and different objects. The method used for intelligent vehicles has good
doi:10.3991/ijoe.v12i03.5154
fatcat:6rbkjnergzb4ro76lngxfuesaa