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Rih-Teng Wu
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Data fusion approaches for structural health monitoring and system identification: Past, present, and future
RT Wu, MR Jahanshahi
Structural Health Monitoring 19 (2), 552-586, 2020
2332020
Deep convolutional neural network for structural dynamic response estimation and system identification
RT Wu, MR Jahanshahi
Journal of Engineering Mechanics 145 (1), 04018125, 2019
2332019
A texture‐based video processing methodology using Bayesian data fusion for autonomous crack detection on metallic surfaces
FC Chen, MR Jahanshahi, RT Wu, C Joffe
Computer‐Aided Civil and Infrastructure Engineering 32 (4), 271-287, 2017
1732017
Deep learning‐based multi‐class damage detection for autonomous post‐disaster reconnaissance
T Ghosh Mondal, MR Jahanshahi, RT Wu, ZY Wu
Structural Control and Health Monitoring 27 (4), e2507, 2020
1452020
Pruning deep convolutional neural networks for efficient edge computing in condition assessment of infrastructures
RT Wu, A Singla, MR Jahanshahi, E Bertino, BJ Ko, D Verma
Computer‐Aided Civil and Infrastructure Engineering 34 (9), 774-789, 2019
1052019
Design of one-dimensional acoustic metamaterials using machine learning and cell concatenation
RT Wu, TW Liu, MR Jahanshahi, F Semperlotti
Structural and Multidisciplinary Optimization 63, 2399-2423, 2021
612021
Deep-Learning-Based Acoustic Metamaterial Design for Attenuating Structure-Borne Noise in Auditory Frequency Bands
TW Liu, CT Chan, RT Wu
Materials 16 (5), 1879, 2023
272023
Intelligent IoT systems for civil infrastructure health monitoring: a research roadmap
E Bertino, MR Jahanshahi, A Singla, RT Wu
Discover Internet of Things 1, 1-11, 2021
242021
A physics-constrained deep learning based approach for acoustic inverse scattering problems
RT Wu, M Jokar, MR Jahanshahi, F Semperlotti
Mechanical Systems and Signal Processing 164, 2022
212022
Two novel approaches to reduce false alarm due to non‐earthquake events for on‐site earthquake early warning system
TY Hsu, RT Wu, KC Chang
Computer‐Aided Civil and Infrastructure Engineering 31 (7), 535-549, 2016
202016
Peak ground acceleration estimation using P-wave parameters and horizontal-to-vertical spectral ratios
TY Hsu, RT Wu, CW Liang, CH Kuo, CM Lin
Terr. Atmos. Ocean. Sci 31 (1), 1-8, 2020
162020
Evaluation of bridge instability caused by dynamic scour based on fractal theory
TK Lin, RT Wu, KC Chang, YS Chang
Smart materials and structures 22 (7), 075003, 2013
132013
Crack segmentation in high-resolution images using cascaded deep convolutional neural networks and Bayesian data fusion
MRJ Wen Tang, Rih-Teng W
Smart Structures and Systems 29 (1), 221-235, 2022
7*2022
Building manufacturing deep learning models with minimal and imbalanced training data using domain adaptation and data augmentation
AS Li, E Bertino, RT Wu, TY Wu
2023 IEEE International Conference on Industrial Technology (ICIT), 1-8, 2023
62023
Performance of Reinforced Concrete Buildings in the 2016 Taiwan (Meinong) Earthquake
S Pujol, A Irfanoglu, M Jahanshahi, L Laughery, A Puranam, LH Cheng, ...
(No Title), 2017
52017
Multi-task deep learning for crack segmentation and quantification in RC structures
YC Chen, RT Wu, A Puranam
Automation in Construction 166, 105599, 2024
42024
Ensemble-based deep learning for autonomous bridge component and damage segmentation leveraging Nested Reg-UNet
A Subedi, W Tang, TG Mondal, RT Wu, MR Jahanshahi
Smart Structures and Systems 31 (4), 335-349, 2023
4*2023
Deep learning-based post-disaster building inspection with channel-wise attention and semi-supervised learning
W Tang, TG Mondal, RT Wu, A Subedi, MR Jahanshahi
Smart Structures and Systems 31 (4), 365-381, 2023
3*2023
Pruning deep neural networks for efficient edge computing in internet of things: A structural health monitoring case study
RIHT WU, A SINGLA, MR JAHANSHAHI, E BERTINO
Structural Health Monitoring 2019, 2019
32019
Development of a high-fidelity failure prediction system for reinforced concrete bridge columns using generative adversarial networks
TY Wu, RT Wu, PH Wang, TK Lin, KC Chang
Engineering Structures 286, 116130, 2023
22023
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