Pixel-Level Fatigue Crack Segmentation in Large-Scale Images of Steel Structures Using an Encoder–Decoder Network

Fatigue cracks are critical types of damage in steel structures due to repeated loads and distortion effects. Fatigue crack growth may lead to further structural failure and even induce collapse. Efficient and timely fatigue crack detection and segmentation can support condition assessment, asset ma...

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Vydané v:	Sensors (Basel, Switzerland) Ročník 21; číslo 12; s. 4135
Hlavní autori:	Dong, Chuanzhi, Li, Liangding, Yan, Jin, Zhang, Zhiming, Pan, Hong, Catbas, Fikret Necati
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 16.06.2021 MDPI
Predmet:	Accuracy Algorithms Bridges computer vision Crack propagation Datasets Decision making Decision theory Decision trees Deep learning fatigue crack Infrastructure Machine learning Metal fatigue Neural networks Nondestructive testing Propagation semantic segmentation steel structures Stress concentration Support vector machines
ISSN:	1424-8220, 1424-8220
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