Ruhua Wang
- (2023): A novel transformer-based semantic segmentation framework for structural condition assessment. In: Structural Health Monitoring, v. 23, n. 2 (July 2023).
- (2022): Structural damage quantification using ensemble‐based extremely randomised trees and impulse response functions. In: Structural Control and Health Monitoring, v. 29, n. 10 (13 September 2022).
- (2021): Densely connected convolutional networks for vibration based structural damage identification. In: Engineering Structures, v. 245 (October 2021).
- (2021): Deep residual network framework for structural health monitoring. In: Structural Health Monitoring, v. 20, n. 4 (April 2021).
- (2017): Development and application of a deep learning–based sparse autoencoder framework for structural damage identification. In: Structural Health Monitoring, v. 18, n. 1 (December 2017).
- (2021): Development and application of random forest technique for element level structural damage quantification. In: Structural Control and Health Monitoring, v. 28, n. 3 (5 February 2021).
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