Research Advance of Crack Detection for Infrastructure Surfaces Based on Deep Learning
Civil infrastructure is prone to changes in physical or performance after long-term use,and causing certain damage to the function and service safety.So it is essential to monitor structure healthy of such facilities.Crack detection is an extremely important part of structure healthy monitoring.Timely detection and identification of such damage can effectively avoid severe accidents.Crack detection methods based on computer vision are simple,fast and accurate,and are widely used for surface crack detection in civil infrastructures.This paper reviews crack detection methods for infra-structure surfaces based on deep learning from three different detection directions:image classification,object detection,and semantic segmentation.And common data collection methods and commonly used public crack datasets are summa-rized.Finally,the difficulties and challenges of deep learning-based surface crack detection methods for infrastructures are discussed,and possible future development directions are envisioned.
structure health monitoringcrack detectioncomputer visiondeep leaning
万方数据
维普
