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Cited by 304Infrastructure Maintenance and MonitoringAsphalt Pavement Performance EvaluationIndustrial Vision Systems and Defect Detection

Image Based Techniques for Crack Detection, Classification and Quantification in Asphalt Pavement: A Review

Zakeri, H., Nejad, Fereidoon Moghadas, Fahimifar, Ahmad·2017·Archives of Computational Methods in Engineering
DOI 10.1007/s11831-016-9194-z
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References 300 · Cited by 304

Authors
Zakeri, H., Nejad, F. M., & Fahimifar, A.
Affiliations
Amirkabir University of Technology (IR)
Corresponding author
Nejad, Fereidoon Moghadas
ORCID
Venue
Archives of Computational Methods in Engineering
Publisher
Springer Science and Business Media LLC
Published
2016-09-17
Volume
24
Issue
4
Pages
935-977
ISSN
  • 1134-3060 (ISSN-L)
  • 1886-1784
DOI
10.1007/s11831-016-9194-z
OpenAlex
W2520959394
Cited by
304
References
300
Citations by year
2026: 31 · 2025: 39 · 2024: 51 · 2023: 41 · 2022: 41 · 2021: 40 · 2020: 28 · 2019: 15 · 2018: 15 · 2017: 2 · 2016: 1
FWCI
14.95
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (unspecified)
Locations
Archives of Computational Methods in Engineering (publishedVersion)
Topics
  • Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
  • Physical Sciences › Engineering › Civil and Structural Engineering › Asphalt Pavement Performance Evaluation
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
Keywords
asphalt pavement, surface cracking, crack detection, crack classification, crack quantification, image processing, pavement distress, pavement management systems, automated pavement inspection, pavement condition assessment

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