- A mathematical-mechanical hybrid driven approach for determining the deformation monitoring indexes of concrete dam. In: Engineering Structures, v. 277 (Februar 2023). (2023):
- An integrated underwater structural multi-defects automatic identification and quantification framework for hydraulic tunnel via machine vision and deep learning. In: Structural Health Monitoring, v. 22, n. 4 (Dezember 2022). (2022):
- Underwater crack pixel-wise identification and quantification for dams via lightweight semantic segmentation and transfer learning. In: Automation in Construction, v. 144 (Dezember 2022). (2022):
- BIM and ontology-based knowledge management for dam safety monitoring. In: Automation in Construction, v. 145 (Januar 2023). (2023):
- Dam safety assessment through data-level anomaly detection and information fusion. In: Structural Health Monitoring, v. 22, n. 3 (September 2022). (2022):
- Unsupervised dam anomaly detection with spatial–temporal variational autoencoder. In: Structural Health Monitoring, v. 22, n. 1 (November 2019). (2019):
- Data-driven crack behavior anomaly identification method for concrete dams in long-term service using offline and online change point detection. In: Journal of Civil Structural Health Monitoring, v. 11, n. 5 (6 September 2021). (2021):
- A new dam structural response estimation paradigm powered by deep learning and transfer learning techniques. In: Structural Health Monitoring, v. 21, n. 3 (August 2021). (2021):