A deep-learning-based approach towards identifying combined faults in structural health monitoring

被引：0
|
作者：
Al-Nasser, Heba [1 ]
Al-Zuriqat, Thamer [1 ]
Dragos, Kosmas [1 ]
Chillón Geck, Carlos [1 ]
Smarsly, Kay [1 ]
机构：
[1] Institute of Digital and Autonomous Construction, Hamburg University of Technology, Germany
来源：
e-Journal of Nondestructive Testing | 2024年 / 29卷 / 07期
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D O I：
10.58286/29588
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学科分类号：
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