Arithmetic-interval method of finding similar features to reduce data for use in computer vision

Autor:	Artur Wiliński
Rok vydání:	2018
Předmět:	Set (abstract data type) Reduction (complexity) Basis (linear algebra) Computer science Interval method Algorithm
Zdroj:	AIP Conference Proceedings.
ISSN:	0094-243X
DOI:	10.1063/1.5043765
Popis:	This paper shows some arithmetic-interval method of finding similar features inside of datasets, and, on this basis, reduction of data. Two algorithms were used, which of the two different data sets (e.g. images), M1 and M2, with elements si j ∈ ℝ, allow you to exclude a significant set of attributes. These methods allows you generate the strongest and least different specific set of k-features f j of two images (data sets) from each other.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::41a2e26afd40ee8901017fc183a4b2eb https://doi.org/10.1063/1.5043765 Zobrazit plný text záznamu