Representation Forms Of 3d Data- Objects

dc.contributor.authorBeknazarova Saida Safibullayevna
dc.contributor.authorAnvarxo’jaev Sarvarxo’ja A’zamxo’ja o’g’li
dc.date.accessioned2026-01-01T12:08:23Z
dc.date.issued2022-03-01
dc.description.abstractmachine learning methods are increasingly resorted to to solve this issue. If we imagine the work of a machine learning algorithm in the form of a "black box", to which data of a given type is fed to the input and the algorithm outputs a prediction in the form of data of a given type, then if data encoding three-dimensional structures are presented at the input and/or output, we talk about the field of machine learning, which is called 3D ML (three dimensional data machine learning problems) or, the term Geometric deep learning is often found when it comes to the use of deep architectures.
dc.formatapplication/pdf
dc.identifier.urihttps://zienjournals.com/index.php/tjm/article/view/904
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/62777
dc.language.isoeng
dc.publisherZien Journals
dc.relationhttps://zienjournals.com/index.php/tjm/article/view/904/735
dc.rightshttps://creativecommons.org/licenses/by-nc/4.0
dc.sourceTexas Journal of Multidisciplinary Studies; Vol. 5 (2022): TJM; 309-311
dc.source2770-0003
dc.subjectoften
dc.subjectmethods
dc.subjectincreasingly
dc.subjectarchitectures
dc.titleRepresentation Forms Of 3d Data- Objects
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

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