Discovery and Classification of Defects on Facing Brick Specimens Using a Convolutional Neural Network

Discovery and Classification of Defects on Facing Brick Specimens Using a Convolutional Neural Network

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 implemented using convolutional neural networks. Using...

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Bibliografische gegevens
Hoofdauteurs: 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
Formaat: Artikel
Taal:English
Gepubliceerd in: MDPI AG 2023-04-01
Reeks:Applied Sciences
Onderwerpen:
computer vision
convolutional neural network
detection
classification
data augmentation
facing bricks
Online toegang:https://www.mdpi.com/2076-3417/13/9/5413

Internet

https://www.mdpi.com/2076-3417/13/9/5413

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