Mohamad Alipour 
- (2022): Integrating visual sensing and structural identification using 3D-digital image correlation and topology optimization to detect and reconstruct the 3D geometry of structural damage. In: Structural Health Monitoring, v. 21, n. 6 (März 2022).
- (2021): Mapping textual descriptions to condition ratings to assist bridge inspection and condition assessment using hierarchical attention. In: Automation in Construction, v. 129 (September 2021).
- (2020): A big data analytics strategy for scalable urban infrastructure condition assessment using semi-supervised multi-transform self-training. In: Journal of Civil Structural Health Monitoring, v. 10, n. 2 (März 2020).
- (2020): Increasing the robustness of material-specific deep learning models for crack detection across different materials. In: Engineering Structures, v. 206 (März 2020).
- (2019): Robust Pixel-Level Crack Detection Using Deep Fully Convolutional Neural Networks. In: Journal of Computing in Civil Engineering, v. 33, n. 6 (November 2019).
- : The Citizen Engineer: Urban Infrastructure Monitoring via Crowd-Sourced Data Analytics. Vorgetragen bei: Structures Congress 2017, April 6–8, 2017, Denver, Colorado.
- (2017): Pattern Recognition in the National Bridge Inventory for Automated Screening and the Assessment of Infrastructure. Vorgetragen bei: Structures Congress 2017, April 6–8, 2017, Denver, Colorado.
- : Numerical Investigation of the Shear Buckling and Post-Buckling of Thin Steel Plates with FRP Strengthening. Vorgetragen bei: Structures Congress 2017, April 6–8, 2017, Denver, Colorado.
- (2019): A hybrid experimental-numerical approach for load rating of reinforced concrete bridges with insufficient structural properties. In: 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. In: Journal of Bridge Engineering (ASCE), v. 24, n. 4 (April 2019).
- (2018): A nondestructive method for load rating of bridges without structural properties and plans. In: Engineering Structures, v. 171 (September 2018).
- (2017): Load-Capacity Rating of Bridge Populations through Machine Learning: Application of Decision Trees and Random Forests. In: Journal of Bridge Engineering (ASCE), v. 22, n. 10 (Oktober 2017).
- (2018): Identification of Flexural Rigidity in Bridges with Limited Structural Information. In: Journal of Structural Engineering (ASCE), v. 144, n. 8 (August 2018).
Structurae kooperiert mit
