Unsupervised machine and deep learning methods for structural damage detection: A comparative study
Author:
Affiliation:
1. Suzhou Institute of Building Science Group Suzhou Jiangsu China
2. Department of Civil Engineering University of Manitoba Winnipeg Manitoba Canada
Publisher
Wiley
Subject
General Medicine
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/eng2.12551
Reference47 articles.
1. Structural Health Monitoring
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4. BarthorpeRJ.On Model‐and Data‐Based Approaches to Structural Health Monitoring. Doctoral thesis. University of Sheffield Sheffield UK;2010.
5. Operational and defect parameters concerning the acoustic-laser vibrometry method for FRP-reinforced concrete
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