Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Daniyar Nurseitov"'
Autor:
Jan Cukor, František Havránek, Sergei Sokolov, Vlastimil Skoták, Lucie Hambálková, Richard Ševčík, Zdeněk Vacek, Daniyar Nurseitov
Publikováno v:
Journal of Forest Science, Vol 68, Iss 11, Pp 452-458 (2022)
Data on wildlife abundance is an important indicator both for the species concerned and the stability of entire ecosystems as well as for sustainable game management. Therefore, the abundance of ungulate game was verified in a foothill region of Kaza
Externí odkaz:
https://doaj.org/article/5016a3fd3af2456abcdaec4c2ea5faf4
Publikováno v:
Journal of Imaging, Vol 6, Iss 12, p 141 (2020)
This article considers the task of handwritten text recognition using attention-based encoder–decoder networks trained in the Kazakh and Russian languages. We have developed a novel deep neural network model based on a fully gated CNN, supported by
Externí odkaz:
https://doaj.org/article/be8899057ebb4fb4a17fe939df3af418
Autor:
Anel Alimova, Daniyar Nurseitov, Daniyar Kurmankhojayev, Rassul Tolegenov, Kairat Bostanbekov, Abdelrahman Abdallah
Publikováno v:
Multimedia Tools and Applications. 80:33075-33097
In this paper, we introduce a large scale dataset, called HKR, to address challenging detection and recognition problems of handwritten Russian and Kazakh text in the scanned documents. We present a new Russian and Kazakh database (with about 95% of
Publikováno v:
Modelling and Simulation in Engineering, Vol 2021 (2021)
A mixed inverse problem for determining the biochemical oxygen demand of water ( L 0 ) and the rate of biochemical oxygen consumption ( k 0 ), which are important indicators of water quality, has been formulated and numerically solved based on real e
Autor:
Maksat Kanatov, Kairat Bostanbekov, Abdelrahman Abdallah, Galymzhan Abdimanap, Daniyar Nurseitov, Anel Alimova
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal. 5:934-943
This article discusses the problem of handwriting recognition in Kazakh and Russian languages. This area is poorly studied since in the literature there are almost no works in this direction. We have tried to describe various approaches and achieveme
Publikováno v:
Scopus-Elsevier
This article presents the Software as a service system that allows creating scenario modeling of pollution transfer for diffuse sources of pollution using the example of the Ili river basin (Republic of Kazakhstan). The development of technologies th
Autor:
A. T. Nurseitova, Anvar Azimov, Daniyar Nurseitov, M. O. Kenzhebayeva, S. Ya. Serovajsky, M. A. Sigalovskiy
Publikováno v:
International Journal of Mathematics and Physics. 10:29-35
Gravimetry is associated with analysis of the gravitational field. The gravitational field is characterized by its potential. This is described by the Poisson equation, the right side of which includes the density of the environment. There exists dir
Publikováno v:
2021 IEEE International Conference on Smart Information Systems and Technologies (SIST).
This paper demonstrates a qualitative evaluation/comparison of face embeddings extracted from deep learning models, such as VGG-Face, Dlib, and OpenFace, on a face discrimination task. While conducting experiments, each of linear SVM (support vector
Autor:
Nazgul Toiganbayeva, Mahmoud Kasem, Galymzhan Abdimanap, Kairat Bostanbekov, Abdelrahman Abdallah, Anel Alimova, Daniyar Nurseitov
Despite the transition to digital information exchange, many documents, such as invoices, taxes, memos and questionnaires, historical data, and answers to exam questions, still require handwritten inputs. In this regard, there is a need to implement
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a9e27ca30d23568392f93e98fb63c23
We present TNCR, a new table dataset with varying image quality collected from free websites. The TNCR dataset can be used for table detection in scanned document images and their classification into 5 different classes. TNCR contains 9428 high-quali
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::547bb7eb360b0a5a42e2dab197d99bda