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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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 2023-04-01
Series:Applied Sciences
Subjects:
computer vision
convolutional neural network
detection
classification
data augmentation
facing bricks
Online Access:https://www.mdpi.com/2076-3417/13/9/5413

Internet

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

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