PERSIST: A New Probabilistic Model For Data Denoising [Articol]

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dc.contributor.authorScrob, Sergiu
dc.date.accessioned2025-07-09T11:25:44Z
dc.date.issued2024
dc.description.abstractThe paper proposes a more efficient solution for reducing the data noise level, using probability estimation for radius-based spatial inference and sampling techniques.
dc.identifier.citationSCROB, Sergiu. PERSIST: A New Probabilistic Model For Data Denoising. In: International Conference dedicated to the 60th anniversary of the foundation of Vladimir Andrunachievici Institute of Mathematics and Computer Science, MSU, October 10-13 2024. Chisinau: [S. n.], 2024, pp. 462-466. ISBN 978-9975-68-515-3.
dc.identifier.isbn978-9975-68-515-3
dc.identifier.urihttps://msuir.usm.md/handle/123456789/18292
dc.language.isoen
dc.subjectdata denoising
dc.subjectprobabilistic model
dc.subjectradiusbasedspatial inference
dc.subjectspatial probability
dc.titlePERSIST: A New Probabilistic Model For Data Denoising [Articol]
dc.typeArticle

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