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Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review
Data-driven methods in structural health monitoring (SHM) is gaining popularity due to recent technological advancements in sensors, as well as high-speed internet and cloud-based computation. Since the introduction of deep learning (DL) in civil engineering, particularly in SHM, this emerging and p...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7294417/ https://www.ncbi.nlm.nih.gov/pubmed/32414205 http://dx.doi.org/10.3390/s20102778 |