Detecting Cracks in Aerated Concrete Samples Using a Convolutional Neural Network

Detecting Cracks in Aerated Concrete Samples Using a Convolutional Neural Network

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 mechanical properties, and solve the problem of detectin...

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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Applied Sciences
Subjects:
convolutional neural network
crack detection
data augmentation
image annotation
aerated concrete
Online Access:https://www.mdpi.com/2076-3417/13/3/1904

Internet

https://www.mdpi.com/2076-3417/13/3/1904

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