Image Based Techniques for Crack Detection, Classification and Quantification in Asphalt Pavement: A Review
By H. Zakeri, Fereidoon Moghadas Nejad, A. Fahimifar. 2017
278 citations recorded by the source corpus.
Subfields: Civil and Structural Engineering, Industrial and Manufacturing Engineering
View Paper: https://www.semanticscholar.org/paper/46d9febd21be448036cebc413ac5d44d4c7de7f3
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In Civil and Structural Engineering
In Industrial and Manufacturing Engineering
Citations in the corpus
- A systematic review of convolutional neural network-based structural condition assessment techniques (2021, background): “A suite of 74 image-based crack acquisition, processing, and interpretation techniques specifically for asphalt 75 pavement was presented by Zakeri et al. (2017).”
- Ensemble of Deep Convolutional Neural Networks for Automatic Pavement Crack Detection and Measurement (2020, background): “noisy pixels. Compared with the closing operation, the opening operation has an adverse order with regards to the erosion and dilation operation. The opening operation is defined as ����𝑖��:((�⊖ψ)⊕ψ) (7) Image segmentation is the attribution of different labels to different regions of an image. The”