Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Irina Razveeva"'
Autor:
Alexey N. Beskopylny, Sergey A. Stel’makh, Evgenii M. Shcherban’, Irina Razveeva, Alexey Kozhakin, Besarion Meskhi, Andrei Chernil’nik, Diana Elshaeva, Oksana Ananova, Mikhail Girya, Timur Nurkhabinov, Nikita Beskopylny
Publikováno v:
Sensors, Vol 24, Iss 13, p 4373 (2024)
The search for structural and microstructural defects using simple human vision is associated with significant errors in determining voids, large pores, and violations of the integrity and compactness of particle packing in the micro- and macrostruct
Externí odkaz:
https://doaj.org/article/81f7971ee95a4a6eb95ea6ba182a21c6
Autor:
Alexey N. Beskopylny, Sergey A. Stel’makh, Evgenii M. Shcherban’, Irina Razveeva, Alexey Kozhakin, Anton Pembek, Tatiana N. Kondratieva, Diana Elshaeva, Andrei Chernil’nik, Nikita Beskopylny
Publikováno v:
Buildings, Vol 14, Iss 5, p 1198 (2024)
In recent years, one of the most promising areas in modern concrete science and the technology of reinforced concrete structures is the technology of vibro-centrifugation of concrete, which makes it possible to obtain reinforced concrete elements wit
Externí odkaz:
https://doaj.org/article/7eb7cf38963b45e8a16c290429abe316
Autor:
Alexey N. Beskopylny, Sergey A. Stel’makh, Evgenii M. Shcherban’, Levon R. Mailyan, Besarion Meskhi, Irina Razveeva, Alexey Kozhakin, Anton Pembek, Diana Elshaeva, Andrei Chernil’nik, Nikita Beskopylny
Publikováno v:
Buildings, Vol 14, Iss 2, p 377 (2024)
The determination of mechanical properties for different building materials is a highly relevant and practical field of application for machine learning (ML) techniques within the construction sector. When working with vibrocentrifuged concrete produ
Externí odkaz:
https://doaj.org/article/6fa1b52c8c3448a29cdf48867496d3d6
Autor:
Irina Razveeva, Alexey Kozhakin, Alexey N. Beskopylny, Sergey A. Stel’makh, Evgenii M. Shcherban’, Sergey Artamonov, Anton Pembek, Himanshu Dingrodiya
Publikováno v:
Buildings, Vol 13, Iss 12, p 3014 (2023)
Currently, artificial intelligence (AI) technologies are becoming a strategic vector for the development of companies in the construction sector. The introduction of “smart solutions” at all stages of the life cycle of building materials, product
Externí odkaz:
https://doaj.org/article/49a7f894cb04498b81f3c8bd5a520b3e
Autor:
Alexey N. Beskopylny, Anton Chepurnenko, Besarion Meskhi, Sergey A. Stel’makh, Evgenii M. Shcherban’, Irina Razveeva, Alexey Kozhakin, Kirill Zavolokin, Andrei A. Krasnov
Publikováno v:
Biomimetics, Vol 8, Iss 3, p 309 (2023)
Fluid particle detection technology is of great importance in the oil and gas industry for improving oil-refining techniques and in evaluating the quality of refining equipment. The article discusses the process of creating a computer vision algorith
Externí odkaz:
https://doaj.org/article/774f7418383946808cad8d375674b956
Autor:
Alexey N. Beskopylny, Evgenii M. Shcherban’, Sergey A. Stel’makh, Levon R. Mailyan, Besarion Meskhi, Irina Razveeva, Alexey Kozhakin, Diana El’shaeva, Nikita Beskopylny, Gleb Onore
Publikováno v:
Applied Sciences, Vol 13, Iss 9, p 5413 (2023)
In recent years, visual automatic non-destructive testing using machine vision algorithms has been widely used in industry. This approach for detecting, classifying, and segmenting defects in building materials and structures can be effectively imple
Externí odkaz:
https://doaj.org/article/1f6b795968d44489bb7331dba3dad6fc
Autor:
Alexey N. Beskopylny, Evgenii M. Shcherban’, Sergey A. Stel’makh, Levon R. Mailyan, Besarion Meskhi, Irina Razveeva, Alexey Kozhakin, Diana El’shaeva, Nikita Beskopylny, Gleb Onore
Publikováno v:
Applied Sciences, Vol 13, Iss 3, p 1904 (2023)
The creation and training of artificial neural networks with a given accuracy makes it possible to identify patterns and hidden relationships between physical and technological parameters in the production of unique building materials, predict mechan
Externí odkaz:
https://doaj.org/article/5ce44850062c441f8c1547d450b616e8
Autor:
Alexey N. Beskopylny, Sergey A. Stel’makh, Evgenii M. Shcherban’, Levon R. Mailyan, Besarion Meskhi, Irina Razveeva, Andrei Chernil’nik, Nikita Beskopylny
Publikováno v:
Applied Sciences, Vol 12, Iss 21, p 10864 (2022)
Currently, one of the topical areas of application of machine learning methods in the construction industry is the prediction of the mechanical properties of various building materials. In the future, algorithms with elements of artificial intelligen
Externí odkaz:
https://doaj.org/article/79d7a5f814494f629bbd0c94b2878cbd
Autor:
Sergey A. Stel’makh, Evgenii M. Shcherban’, Alexey N. Beskopylny, Levon R. Mailyan, Besarion Meskhi, Irina Razveeva, Alexey Kozhakin, Nikita Beskopylny
Publikováno v:
Materials; Volume 15; Issue 19; Pages: 6740
Currently, one of the topical areas of application of artificial intelligence methods in industrial production is neural networks, which allow for predicting the performance properties of products and structures that depend on the characteristics of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::999d299c3e28c100dcb2e534f0e32bcb
Publikováno v:
E3S Web of Conferences. 363:02026
Currently, one of the topical areas of application of artificial intelligence methods in ensuring environmental monitoring of water resources is the analysis of Earth remote sensing images in order to control and prevent potentially dangerous changes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e0e9acd234cfc96aa70a6f27d5faecc
https://doi.org/10.1051/e3sconf/202236302026
https://doi.org/10.1051/e3sconf/202236302026