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• W2048490443 abstract "In this paper, a genetic tracker with adaptive neuro-fuzzy inference system (GT-ANFIS) is presented for multiple target tracking (MTT). First, the data association problem, formulated as an N-dimensional assignment problem, is solved using the genetic algorithm (GA), and then the inaccuracies in the estimation are corrected by the adaptive neuro-fuzzy inference system (ANFIS). The performances of the GT-ANFIS, the joint probabilistic data association filter (JPDAF), the genetic tracker (GT), and the genetic tracker with neural network (GT-NN) are compared with each other for six different tracking scenarios. It was shown that the tracks estimated by using proposed GT-ANFIS agree better with the true tracks than the tracks predicted by the JPDAF, the GT, and the GT-NN." @default.
• W2048490443 created "2016-06-24" @default.
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• W2048490443 date "2008-11-01" @default.
• W2048490443 modified "2023-09-25" @default.
• W2048490443 title "Genetic tracker with adaptive neuro-fuzzy inference system for multiple target tracking" @default.
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• W2048490443 doi "https://doi.org/10.1016/j.eswa.2007.08.065" @default.
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