Concrete crack detection using context‐aware deep semantic segmentation network-Reference-Cited by-同舟云学术

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Concrete crack detection using context‐aware deep semantic segmentation network

Published:2019-07-16 Issue:11 Volume:34 Page:951-971
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer‐Aided Civil and Infrastructure Engineering

Author:

Zhang Xinxiang¹,Rajan Dinesh¹,Story Brett²

Affiliation:

1. Department of Electrical and Computer EngineeringSouthern Methodist University Dallas TX USA

2. Department of Civil and Environmental EngineeringSouthern Methodist University Dallas TX USA

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12477

Reference69 articles.

1. Automatic Pixel-Level Pavement Crack Detection Using Information of Multi-Scale Neighborhoods

2. Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection

3. Avila M. Begot S. Duculty F. &Nguyen T. S.(2014).2D image based road pavement crack detection by calculating minimal paths and dynamic programming. InProceedings of IEEE International Conference on Image Processing (ICIP) pp.783–787.

4. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

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