Comparison of image recognition efficiency of Bayes, correlation, and modified Hopfield network algorithms
- Авторы: Basistov Y.A.1, Yanovskii Y.G.1
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Учреждения:
- Institute of Applied Mechanics
- Выпуск: Том 26, № 4 (2016)
- Страницы: 697-704
- Раздел: 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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Аннотация
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.
Об авторах
Yu. Basistov
Institute of Applied Mechanics
Автор, ответственный за переписку.
Email: iam@iam.ras.ru
Россия, Moscow, 119991
Yu. Yanovskii
Institute of Applied Mechanics
Email: iam@iam.ras.ru
Россия, Moscow, 119991
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