A general framework for supervised structural health monitoring and sensor output validation mitigating data imbalance with generative adversarial networks-generated high-dimensional features
| Autor(en): |
Mohammad Hesam Soleimani-Babakamali
(Department of Civil and Environmental Engineering, Virginia Tech University, Blacksburg, VA, USA)
Roksana Soleimani-Babakamali (Department of Computer Science, University of Vienna, Vienna, Austria) Rodrigo Sarlo 
(Department of Civil and Environmental Engineering, Virginia Tech University, Blacksburg, VA, USA)
|
|---|---|
| Medium: | Fachartikel |
| Sprache(n): | Englisch |
| Veröffentlicht in: | Structural Health Monitoring, August 2021, n. 3, v. 21 |
| Seite(n): | 147592172110254 |
| DOI: | 10.1177/14759217211025488 |
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Datenseite - Reference-ID
10627261 - Veröffentlicht am:
05.09.2021 - Geändert am:
09.05.2022
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