10 June 2013 Position-independent ATR using hierarchical hidden Markov model as the identification algorithm
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Abstract
A recursive algorithm based on hidden Markov models is used to build a model of the identification target. The end result of the recursive matching is an optimal scene-to-model transformation, along with a recognition degree of suitability value between the scene and the model. The hierarchical structure of the model allows a maximization of the target identification probability.
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Andre Sokolnikov, Andre Sokolnikov, } "Position-independent ATR using hierarchical hidden Markov model as the identification algorithm", Proc. SPIE 8744, Automatic Target Recognition XXIII, 87440B (10 June 2013); doi: 10.1117/12.2017037; https://doi.org/10.1117/12.2017037
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