Deep learning-based concrete defects classification and detection using semantic segmentation

Visual damage detection of infrastructure using deep learning (DL)-based computational approaches can facilitate a potential solution to reduce subjectivity yet increase the accuracy of the damage diagnoses and accessibility in a structural health monitoring (SHM) system. However, despite remarkable...

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Bibliographic Details

Published in:	Structural health monitoring Vol. 23; no. 1; p. 383
Main Authors:	Arafin, Palisa, Billah, Ahm Muntasir, Issa, Anas
Format:	Journal Article
Language:	English
Published:	England 01.01.2024
Subjects:	encoder-decoder model structural health monitoring semantic segmentation convolutional neural network Concrete defects
ISSN:	1475-9217
Online Access:	Get more information
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