| Lost data recovery for structural health monitoring based on convolutional neural networks G Fan, J Li, H Hao Structural Control and Health Monitoring 26 (10), e2433, 2019 | 149 | 2019 |
| Vibration signal denoising for structural health monitoring by residual convolutional neural networks G Fan, J Li, H Hao Measurement 157, 107651, 2020 | 137 | 2020 |
| Data driven structural dynamic response reconstruction using segment based generative adversarial networks G Fan, J Li, H Hao, Y Xin Engineering Structures 234, 111970, 2021 | 110 | 2021 |
| Dynamic response reconstruction for structural health monitoring using densely connected convolutional networks G Fan, J Li, H Hao Structural Health Monitoring 20 (4), 1373-1391, 2021 | 101 | 2021 |
| Improved automated operational modal identification of structures based on clustering G Fan, J Li, H Hao Structural Control and Health Monitoring 26 (12), e2450, 2019 | 54 | 2019 |
| Structural dynamic response reconstruction using self-attention enhanced generative adversarial networks G Fan, Z He, J Li Engineering Structures 276, 115334, 2023 | 42 | 2023 |
| Improving completeness and accuracy of 3D point clouds by using deep learning for applications of digital twins to civil structures S Chen, G Fan, J Li Advanced Engineering Informatics 58, 102196, 2023 | 17 | 2023 |
| Structural health monitoring data anomaly detection by transformer enhanced densely connected neural networks J Li, W Chen, G Fan Smart Struct. Syst. 30 (6), 613-626, 2022 | 10 | 2022 |
| Numerical and experimental verifications on damping identification with model updating and vibration monitoring data J Li, H Hao, G Fan, P Ni, X Wang, C Wu, JM Lee, KH Jung Smart Structures and Systems 20 (2), 127-137, 2017 | 10 | 2017 |
| A systematic approach to pixel-level crack detection and localization with a feature fusion attention network and 3D reconstruction Q Zeng, G Fan, D Wang, W Tao, A Liu Engineering Structures 300, 117219, 2024 | 8 | 2024 |
| Structural health monitoring response reconstruction based on UAGAN under structural condition variations with few-shot learning J Li, Z He, G Fan Smart structures and systems 30 (6), 687-701, 2022 | 7 | 2022 |
| Deep learning for automated multiclass surface damage detection in bridge inspections L Huang, G Fan, J Li, H Hao Automation in Construction 166, 105601, 2024 | 5 | 2024 |
| Using deep learning technique for recovering the lost measurement data G Fan, J Li, H Hao EASEC16: Proceedings of The 16th East Asian-Pacific Conference on Structural …, 2021 | 4 | 2021 |
| Using deep learning technique for non-model based vibration response reconstruction G Fan, J Li, H Hao Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and …, 2021 | 2 | 2021 |
| An Improved SSI Approach for Structural Modal Identification J Li, G Fan, H Hao, H Li ACMSM25: Proceedings of the 25th Australasian Conference on Mechanics of …, 2020 | 1 | 2020 |
| Missing data imputation for structural health monitoring using unsupervised domain adaptation and pretraining techniques W Zheng, J Li, H Hao, G Fan Engineering Structures 328, 119694, 2025 | | 2025 |
| Automatic complex concrete crack detection and quantification based on point clouds and deep learning S Chen, G Fan, J Li, H Hao Engineering Structures 327, 119635, 2025 | | 2025 |
| Systematical vibration data recovery based on novel convolutional self-attention networks G Fan, D Zhang, M Hu, J Li, H Hao Journal of Civil Structural Health Monitoring, 1-21, 2024 | | 2024 |
| Clustering and Deep Learning Techniques for Structural Health Monitoring G Fan Curtin University, 2020 | | 2020 |
