Yangtao Li 
- (2024): BIM-based framework of automatic tunnel segment assembly and deviation control. Dans: Underground Space, v. 16 (juin 2024).
- (2023): Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning technology. Dans: Frontiers of Structural and Civil Engineering, v. 17, n. 8 (août 2023).
- (2023): A real-time multi-defect automatic identification framework for concrete dams via improved YOLOv5 and knowledge distillation. Dans: Journal of Civil Structural Health Monitoring, v. 13, n. 6-7 (juin 2023).
- (2023): A Coupled Model for Dam Foundation Seepage Behavior Monitoring and Forecasting Based on Variational Mode Decomposition and Improved Temporal Convolutional Network. Dans: Structural Control and Health Monitoring, v. 2023 (février 2023).
- (2023): A mathematical-mechanical hybrid driven approach for determining the deformation monitoring indexes of concrete dam. Dans: Engineering Structures, v. 277 (février 2023).
- (2022): An integrated underwater structural multi-defects automatic identification and quantification framework for hydraulic tunnel via machine vision and deep learning. Dans: Structural Health Monitoring, v. 22, n. 4 (décembre 2022).
- (2023): A robust real‐time method for identifying hydraulic tunnel structural defects using deep learning and computer vision. Dans: Computer-Aided Civil and Infrastructure Engineering, v. 38, n. 10 (6 juin 2023).
- (2022): Underwater crack pixel-wise identification and quantification for dams via lightweight semantic segmentation and transfer learning. Dans: Automation in Construction, v. 144 (décembre 2022).
- (2023): BIM and ontology-based knowledge management for dam safety monitoring. Dans: Automation in Construction, v. 145 (janvier 2023).
- (2022): Dam safety assessment through data-level anomaly detection and information fusion. Dans: Structural Health Monitoring, v. 22, n. 3 (septembre 2022).
- (2019): Unsupervised dam anomaly detection with spatial–temporal variational autoencoder. Dans: Structural Health Monitoring, v. 22, n. 1 (novembre 2019).
- (2021): Data-driven crack behavior anomaly identification method for concrete dams in long-term service using offline and online change point detection. Dans: Journal of Civil Structural Health Monitoring, v. 11, n. 5 (6 septembre 2021).
- (2021): A new dam structural response estimation paradigm powered by deep learning and transfer learning techniques. Dans: Structural Health Monitoring, v. 21, n. 3 (août 2021).
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