Conditional assessment of large-scale infrastructure systems using deep learning approaches (Conference Presentation)

Hong Pan; Zi Zhang; Qi Cao; Xingyu Wang; Zhibin Lin

doi:10.1117/12.2560133

27 April 2020 Conditional assessment of large-scale infrastructure systems using deep learning approaches (Conference Presentation)

Hong Pan, Zi Zhang, Qi Cao, Xingyu Wang, Zhibin Lin

Author Affiliations +

Proceedings Volume 11382, Smart Structures and NDE for Industry 4.0, Smart Cities, and Energy Systems; 113820T (2020) https://doi.org/10.1117/12.2560133
Event: SPIE Smart Structures + Nondestructive Evaluation, 2020, Online Only

Abstract

Assessment of health state of large-scale infrastructure systems are crucial to ensure their operational safety. In this study, we propose the image-based conditional assessment of large-scale systems using deep learning approaches. The deep convolutional neural networks are optimally designed for satellite images to extract the sensitive features for assessment. The findings show that the machine learning methods exhibit great potential for infrastructure assessment, such as high bridges, and oil/gas pipeline assessment at both spatial and temporary scales over conventional methods.

Conference Presentation

Citation Download Citation

Hong Pan, Zi Zhang, Qi Cao, Xingyu Wang, and Zhibin Lin "Conditional assessment of large-scale infrastructure systems using deep learning approaches (Conference Presentation)", Proc. SPIE 11382, Smart Structures and NDE for Industry 4.0, Smart Cities, and Energy Systems, 113820T (27 April 2020); https://doi.org/10.1117/12.2560133

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