Unsupervised domain adaptation-based crack segmentation using transformer network-Reference-Cited by-同舟云学术

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Unsupervised domain adaptation-based crack segmentation using transformer network

Published:2023-12 Issue: Volume:80 Page:107889
ISSN:2352-7102
Container-title:Journal of Building Engineering
language:en
Short-container-title:Journal of Building Engineering

Author:

Beyene Daniel Asefa,Tran Dai Quoc,Maru Michael Bekele^ORCID,Kim Taeheon^ORCID,Park Solmoi^ORCID,Park Seunghee

Funder

Korea Ministry of Science and ICT

Ministry of Land, Infrastructure and Transport

National Research Foundation of Korea

Korea Agency for Infrastructure Technology Advancement

Publisher

Elsevier BV

Subject

Mechanics of Materials,Safety, Risk, Reliability and Quality,Building and Construction,Architecture,Civil and Structural Engineering

Reference71 articles.

1. What’s cracking? A review and analysis of deep learning methods for structural crack segmentation, detection and quantification;König,2022

2. Comparative study on concrete crack detection of tunnel based on different deep learning algorithms;Yu;Front. Earth Sci.,2022

3. Integrated pixel-level CNN-FCN crack detection via photogrammetric 3D texture mapping of concrete structures;Chaiyasarn;Autom. Constr.,2022

4. Structural crack detection using deep convolutional neural networks;Ali;Autom. Constr.,2022

5. A potential crack region method to detect crack using image processing of multiple thresholding;Chen;Signal Image Video Process.,2022

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