Výsledky vyhledávání - "Zhazira Mutalova"

Akademický článek

Development of a Mathematical Model for Detecting Moving Objects in Video Streams in Real-Time

Autor: Zhazira Mutalova, Anargul Shaushenova, Ardak Nurpeisova, Maral Ongarbayeva, Aidar Ispussinov, Sandugash Bekenova, Zhanar Altynbekova

Publikováno v: IEEE Access, Vol 12, Pp 169235-169246 (2024)

The development of mathematical models for detecting moving objects in real-time video streams is a significant task, especially in light of the growing demands for security and process automation. This paper proposes a detection system based on the

Externí odkaz: https://doaj.org/article/a456f819ee964a7bb3fa37ab14c9df5c

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Akademický článek

Research on the Development of a Proctoring System for Conducting Online Exams in Kazakhstan

Autor: Ardak Nurpeisova, Anargul Shaushenova, Zhazira Mutalova, Maral Ongarbayeva, Shakizada Niyazbekova, Anargul Bekenova, Lyazzat Zhumaliyeva, Samal Zhumasseitova

Publikováno v: Computation, Vol 11, Iss 6, p 120 (2023)

The demand for online education is gradually growing. Most universities and other institutions are faced with the fact that it is almost impossible to track how honestly test takers take exams remotely. In online formats, there are many simple opport

Externí odkaz: https://doaj.org/article/751bdc7405e149d082509cdc5fd49351

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Akademický článek

The Study of Mathematical Models and Algorithms for Face Recognition in Images Using Python in Proctoring System

Autor: Ardak Nurpeisova, Anargul Shaushenova, Zhazira Mutalova, Zhandos Zulpykhar, Maral Ongarbayeva, Shakizada Niyazbekova, Alexander Semenov, Leila Maisigova

Publikováno v: Computation, Vol 10, Iss 8, p 136 (2022)

The article analyzes the possibility and rationality of using proctoring technology in remote monitoring of the progress of university students as a tool for identifying a student. Proctoring technology includes face recognition technology. Face reco

Externí odkaz: https://doaj.org/article/2891a8472db440829f68b83501f02c82

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Implementation of machine learning models to determine the appropriate model for protein function prediction

Autor: Yekaterina Golenko, Aisulu Ismailova, Anargul Shaushenova, Zhazira Mutalova, Damir Dossalyanov, Aliya Ainagulova, Akgul Naizagarayeva

Publikováno v: Eastern-European Journal of Enterprise Technologies. 5:42-49

Predicting the function of proteins is a crucial part of genome annotation, which can help in solving a wide range of biological problems. Many methods are available to predict the functions of proteins. However, except for sequence, most features ar

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f5823c1fa7eb20594106833c00ab546f
https://doi.org/10.15587/1729-4061.2022.263270

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