Fully automated natural frequency identification based on deep-learning-enhanced computer vision and power spectral density transmissibility
Author(s): |
Zhi-Wei Chen
Xu-Zhi Ruan (Department of Civil Engineering, Xiamen University, Xiamen, China) Kui-Ming Liu (Department of Civil Engineering, Xiamen University, Xiamen, China) Wang-Ji Yan (State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau, Macau, China) Jian-Tao Liu Dai-Cheng Ye (Xiamen Municipal Baicheng Construction & Investment Co. Ltd, Xiamen, China) |
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Medium: | journal article |
Language(s): | English |
Published in: | Advances in Structural Engineering, June 2022, n. 13, v. 25 |
Page(s): | 136943322211075 |
DOI: | 10.1177/13694332221107572 |
- About this
data sheet - Reference-ID
10678383 - Published on:
18/06/2022 - Last updated on:
19/04/2023