Pixel-level crack segmentation of tunnel lining segments based on an encoder-decoder network

Regular detection and repair for lining cracks are necessary to guarantee the safety and stability of tunnels. The development of computer vision has greatly promoted structural health monitoring. This study proposes a novel encoder-decoder structure, CrackRecNet, for semantic segmentation of lining...

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Veröffentlicht in:	Frontiers of Structural and Civil Engineering Jg. 18; H. 5; S. 681 - 698
Hauptverfasser:	HOU, Shaokang, OU, Zhigang, HUANG, Yuequn, LIU, Yaoru
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Beijing Higher Education Press 01.05.2024 Springer Nature B.V
Schlagworte:	Boring machines Cities Civil Engineering Coders Computer vision Concrete structures convolutional neural network Countries crack detection Cracks Drilling & boring machinery encoder-decoder structure Engineering Flaw detection Image acquisition Image processing Image segmentation Laser range finders Pixels Regions Research Article Semantic segmentation Structural health monitoring Tunnel construction tunnel lining segment Tunnel linings Tunneling shields encoder–decoder structure semantic segmentation tunnel lining segment crack detection convolutional neural network
ISSN:	2095-2430, 2095-2449
Online-Zugang:	Volltext
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