Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete

Construction and Building Materials

Volumn 186, Issue , 2018, Pages 1031-1045

  Dorafshan, Sattar ^a   Thomas, Robert J ^b   Maguire, Marc ^a  

^a Utah State University   (United States)

^b Clarkson University   (United States)

Author keywords

Concrete; Crack detection; Deep learning; Edge detection; Image processing; Neural network; Structural health monitoring; Vision based

Indexed keywords

BINARY IMAGES; CLASSIFICATION (OF INFORMATION); COMPUTATIONAL EFFICIENCY; CONCRETES; CONVOLUTION; DAMAGE DETECTION; DEEP LEARNING; DEEP NEURAL NETWORKS; EDGE DETECTION; IMAGE PROCESSING; NEURAL NETWORKS; STRUCTURAL HEALTH MONITORING;

COMPUTATIONAL TIME; DEEP CONVOLUTIONAL NEURAL NETWORKS; DETECTION METHODS; EDGE DETECTION ALGORITHMS; EDGE DETECTION METHODS; LAPLACIAN OF GAUSSIAN; RELATIVE PERFORMANCE; VISION BASED;

CRACK DETECTION;

EID: 85051379739     PISSN: 09500618     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conbuildmat.2018.08.011     Document Type: Article

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