Comparison of image recognition efficiency of Bayes, correlation, and modified Hopfield network algorithms


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The statistical estimates of the probability of correct recognition of the images, noisy reference by an additive handicap, for Bayes, correlation, and modified Hopfield network algorithms are compared. It is shown that, in the case of complete a priori probability concerning a handicap, the modified Hopfield network algorithm reaches the quality of the Bayes algorithm. At a deviation a priori probability on a handicap, the quality of the Bayes algorithm is worse than that of the modified Hopfield network algorithm. The correlation algorithm is worse than the modified Hopfield network algorithm, in general.

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Yu. Basistov

Institute of Applied Mechanics

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Email: iam@iam.ras.ru
俄罗斯联邦, Moscow, 119991

Yu. Yanovskii

Institute of Applied Mechanics

Email: iam@iam.ras.ru
俄罗斯联邦, Moscow, 119991

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