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The determination of distances between images of objects based on persistent spectra of eigenvalues of Laplace matrices Научная публикация

Журнал Journal of Physics: Conference Series
ISSN: 1742-6588 , E-ISSN: 1742-6596
Вых. Данные Год: 2021, Том: 1901, Номер: 1, Номер статьи : 012033, Страниц : DOI: 10.1088/1742-6596/1901/1/012033
Ключевые слова distance between images; Laplace matrices; persistent spectra of eigenvalues; Vietoris-Rips complex; Wasserstein distance
Авторы Chukanov S.N. 1
Организации
1 Sobolev Institute of Mathematics, Siberian Branch, Russian Academy of Sciences, Omsk Branch, Pevtsova 13, Omsk, 644043, Russian Federation

Информация о финансировании (3)

1 Российский фонд фундаментальных исследований 18-08-01284
2 Российский фонд фундаментальных исследований 18-07-00526
3 Омский филиал ФГБУН «Институт математики им. С.Л. Соболева СО РАН». 0314-2019-0020

Реферат: The work uses the method of filtering simplicial complexes, similar to the method used in the formation of persistent homology. The filtering process creates a number of nested simplicial complexes encoded with topological information. In papers [1-6] algorithms for the formation of persistent barcodes are used to compare images of objects. The use of persistent homology in relation to the methods of traditional algebraic topology provides additional information about the image of an object. To increase the diversity of information and the number of machine learning features, this work proposes algorithms for the formation of persistent spectra of eigenvalues of Laplace matrices for comparing images of objects. When comparing the shapes of objects, it is proposed to construct a modified Wasserstein distance based on the determination of the spectra of the eigenvalues of the Laplace matrix of the compared shapes. © Published under licence by IOP Publishing Ltd.
Библиографическая ссылка: Chukanov S.N.
The determination of distances between images of objects based on persistent spectra of eigenvalues of Laplace matrices
Journal of Physics: Conference Series. 2021. V.1901. N1. 012033 . DOI: 10.1088/1742-6596/1901/1/012033 Scopus OpenAlex
Идентификаторы БД:
Scopus: 2-s2.0-85107378810
OpenAlex: W3164356058
Цитирование в БД:
БД Цитирований
Scopus 1
OpenAlex 2
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