Method for calculating the adequacy parameters of image mathematical model
Problemy fiziki, matematiki i tehniki, no. 3 (2023), pp. 95-99

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A structure of an artificial neural network for assessing the similarity of a pair of images, comparing the quality of its work with other criteria for image similarity are presented. Based on the proposed artificial neural network, a methodology for estimating the adequacy of mathematical image model by the estimation of its similarity to real images has been developed. A comparison of the estimation of the adequacy of the mathematical image model by the classical method and using the proposed methodology on the example of a Gaussian mathematical image model has ben conducted.
Keywords: image modeling, model adequacy estimate, artificial neural networks, similarity estimate.
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     author = {A. V. Sergeyenko and A. Y. Liplyanin and A. V. Khijnyak},
     title = {Method for calculating the adequacy parameters of image mathematical model},
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     pages = {95--99},
     publisher = {mathdoc},
     number = {3},
     year = {2023},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/PFMT_2023_3_a16/}
}
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A. V. Sergeyenko; A. Y. Liplyanin; A. V. Khijnyak. Method for calculating the adequacy parameters of image mathematical model. Problemy fiziki, matematiki i tehniki, no. 3 (2023), pp. 95-99. http://geodesic.mathdoc.fr/item/PFMT_2023_3_a16/