- Optimized structural inspection path planning for automated unmanned aerial systems. Dans: Automation in Construction, v. 168 (décembre 2024). (2024):
- Deep Learning-Based Visual Identification of Signs of Bat Presence in Bridge Infrastructure Images: A Transfer Learning Approach. Dans: Transportation Research Record: Journal of the Transportation Research Board, v. 2675, n. 12 (4 septembre 2021). (2021):
- Integrating visual sensing and structural identification using 3D-digital image correlation and topology optimization to detect and reconstruct the 3D geometry of structural damage. Dans: Structural Health Monitoring, v. 21, n. 6 (mars 2022). (2022):
- Mapping textual descriptions to condition ratings to assist bridge inspection and condition assessment using hierarchical attention. Dans: Automation in Construction, v. 129 (septembre 2021). (2021):
- A big data analytics strategy for scalable urban infrastructure condition assessment using semi-supervised multi-transform self-training. Dans: Journal of Civil Structural Health Monitoring, v. 10, n. 2 (mars 2020). (2020):
- Increasing the robustness of material-specific deep learning models for crack detection across different materials. Dans: Engineering Structures, v. 206 (mars 2020). (2020):
- Robust Pixel-Level Crack Detection Using Deep Fully Convolutional Neural Networks. Dans: Journal of Computing in Civil Engineering, v. 33, n. 6 (novembre 2019). (2019):
- The Citizen Engineer: Urban Infrastructure Monitoring via Crowd-Sourced Data Analytics. Présenté pendant: Structures Congress 2017, April 6–8, 2017, Denver, Colorado. :
- Pattern Recognition in the National Bridge Inventory for Automated Screening and the Assessment of Infrastructure. Présenté pendant: Structures Congress 2017, April 6–8, 2017, Denver, Colorado. (2017):
- Numerical Investigation of the Shear Buckling and Post-Buckling of Thin Steel Plates with FRP Strengthening. Présenté pendant: Structures Congress 2017, April 6–8, 2017, Denver, Colorado. :
- A hybrid experimental-numerical approach for load rating of reinforced concrete bridges with insufficient structural properties. Dans: Structure and Infrastructure Engineering, v. 15, n. 6 (mai 2019). (2019):
- Field Deployment and Laboratory Evaluation of 2D Digital Image Correlation for Deflection Sensing in Complex Environments. Dans: Journal of Bridge Engineering (ASCE), v. 24, n. 4 (avril 2019). (2019):
- A nondestructive method for load rating of bridges without structural properties and plans. Dans: Engineering Structures, v. 171 (septembre 2018). (2018):
- Load-Capacity Rating of Bridge Populations through Machine Learning: Application of Decision Trees and Random Forests. Dans: Journal of Bridge Engineering (ASCE), v. 22, n. 10 (octobre 2017). (2017):
- Identification of Flexural Rigidity in Bridges with Limited Structural Information. Dans: Journal of Structural Engineering (ASCE), v. 144, n. 8 (août 2018). (2018):