Pavement crack detection and classification based on fusion feature of LBP and PCA with SVM-Reference-Cited by-同舟云学术

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Pavement crack detection and classification based on fusion feature of LBP and PCA with SVM

Published:2021-03-23 Issue: Volume: Page:1-10
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Chen Cheng¹,Seo Hyungjoon²^ORCID,Jun Chang Hyun³,Zhao Y.¹

Affiliation:

1. Civil Engineering department, Xi’an Jiao tong-Liverpool University, Suzhou, People’s Republic of China

2. Department of Civil Engineering and Industrial Design, University of Liverpool, Liverpool, UK

3. Department of Civil and Environmental Engineering, Chung-Ang University, Seoul, South Korea

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2021.1888092

Reference19 articles.

1. Deep Metric Learning to Rank

2. Review of Pavement Defect Detection Methods

3. Automatic Pavement Crack Detection Based on Image Recognition

4. Novel Approach to Pavement Cracking Detection Based on Fuzzy Set Theory

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3. Robust Semantic Segmentation for Automatic Crack Detection Within Pavement Images Using Multi-Mixing of Global Context and Local Image Features;IEEE Transactions on Intelligent Transportation Systems;2024-09

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