| DC Field | Value | Language |
|---|
| dc.contributor.author | Pribytko, P. D. | - |
| dc.contributor.author | Shvedova, O. A. | - |
| dc.coverage.spatial | Донецк | ru_RU |
| dc.date.accessioned | 2023-01-20T08:49:31Z | - |
| dc.date.available | 2023-01-20T08:49:31Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.citation | Pribytko, P. D. Automated video surveillance system using neural networks for object recognition / P. D. Pribytko, O. A. Shvedova // Информатика, управляющие системы, математическое и компьютерное моделирование : cборник материалов 13-ой международной научно-технической конференции / Донецкий национальный технический университет. – Донецк, 2022. – С. 228-231. | ru_RU |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/49752 | - |
| dc.description.abstract | The uniqueness of the developed automated system lies in the use of technologies based on neural networks, which allows the equipment to use the “Deep Learning” effect. Considering the unfavorable epidemiological situation, thermal equipment is integrated into the automated system which enables to carry out thermometric measuring when visiting the enterprise. The advantages of this system are such as the following: monitoring the integrity of the protected perimeter, organization of time tracking and organization of preventive measures (COVID). | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | ДонНТУ | ru_RU |
| dc.subject | публикации ученых | ru_RU |
| dc.subject | security systems | ru_RU |
| dc.subject | video surveillance | ru_RU |
| dc.subject | neural network technologies | ru_RU |
| dc.subject | access control and management systems | ru_RU |
| dc.subject | biometric technologies | ru_RU |
| dc.subject | COVID-19 | ru_RU |
| dc.title | Automated video surveillance system using neural networks for object recognition | ru_RU |
| dc.type | Article | ru_RU |
| Appears in Collections: | Публикации в зарубежных изданиях
|
