00 DSpace/Manakin Repository

Convolutional neural networks for the crack diagnostics in concrete structures

Показати скорочений опис матеріалу

dc.contributor.author Danishevskyy, Vladyslav
dc.contributor.author Gaidar, Anastasia
dc.date.accessioned 2024-05-27T11:21:56Z
dc.date.available 2024-05-27T11:21:56Z
dc.date.issued 2024-02
dc.identifier.citation Danishevskyy V. Convolutional neural networks for the crack diagnostics in concrete structures / V. Danishevskyy, A. Gaidar // Матеріали Міжнародної наук.-практ. конференції «Інноваційні технології забезпечення параметрів комфорту, енергоефективності і екологічності житлових будівель на основі смарт-технологій», (20−21 лютого 2024 р., м. Дніпро): зб. тез. - Дніпро: ПДАБА, 2024. – С. 17-20 uk_UA
dc.identifier.uri http://srd.pgasa.dp.ua:8080/xmlui/handle/123456789/13042
dc.description.abstract EN: Problem statement. Millions of dollars are spent annually in the world on technical diagnostics of buildings and structures. Natural disasters such as floods and earthquakes, along with numerous negative man-made impacts lead to serious damage to building structures. The problem of diagnostics of the buildings and structures became extremely urgent after the aggression of the russian federation in Ukraine, which led to large-scale damage and destruction of industrial projects, housing stock and infrastructure projects such as roads, bridges, tunnels, etc. An important and urgent problem of Civil Engineering is to automate the processes of diagnostics of buildings and structures and to develop new methods for identifying building defects in building structures that would save human resources and reduce the dependence of survey results on subjective factors. uk_UA
dc.language.iso en uk_UA
dc.publisher Придніпровська державна академія будівництва та архітектури uk_UA
dc.subject convolutional neural networks uk_UA
dc.subject the crack diagnostics in concrete structures uk_UA
dc.title Convolutional neural networks for the crack diagnostics in concrete structures uk_UA
dc.type Article uk_UA


Долучені файли

Даний матеріал зустрічається у наступних фондах

Показати скорочений опис матеріалу