Representation Forms Of 3d Data- Objects
| dc.contributor.author | Beknazarova Saida Safibullayevna | |
| dc.contributor.author | Anvarxo’jaev Sarvarxo’ja A’zamxo’ja o’g’li | |
| dc.date.accessioned | 2026-01-01T12:08:23Z | |
| dc.date.issued | 2022-03-01 | |
| dc.description.abstract | machine 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.format | application/pdf | |
| dc.identifier.uri | https://zienjournals.com/index.php/tjm/article/view/904 | |
| dc.identifier.uri | https://asianeducationindex.com/handle/123456789/62777 | |
| dc.language.iso | eng | |
| dc.publisher | Zien Journals | |
| dc.relation | https://zienjournals.com/index.php/tjm/article/view/904/735 | |
| dc.rights | https://creativecommons.org/licenses/by-nc/4.0 | |
| dc.source | Texas Journal of Multidisciplinary Studies; Vol. 5 (2022): TJM; 309-311 | |
| dc.source | 2770-0003 | |
| dc.subject | often | |
| dc.subject | methods | |
| dc.subject | increasingly | |
| dc.subject | architectures | |
| dc.title | Representation Forms Of 3d Data- Objects | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
| dc.type | Peer-reviewed Article |
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