Comparison of image recognition efficiency of Bayes, correlation, and modified Hopfield network algorithms
- 作者: Basistov Y.A.1, Yanovskii Y.G.1
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隶属关系:
- Institute of Applied Mechanics
- 期: 卷 26, 编号 4 (2016)
- 页面: 697-704
- 栏目: Representation, Processing, Analysis, and Understanding of Images
- URL: https://bakhtiniada.ru/1054-6618/article/view/194914
- DOI: https://doi.org/10.1134/S1054661816040039
- ID: 194914
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详细
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.
作者简介
Yu. Basistov
Institute of Applied Mechanics
编辑信件的主要联系方式.
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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