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International Journal of Pavement Engineering Volume 23, 2022 - Issue 11
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Articles

Validating the practicality of utilising an image classifier developed using TensorFlow framework in collecting corrugation data from gravel roads

Osama Abu Daouda Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WyomingCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-1829-6204View further author information
ORCID Icon,
Omar Albatayneha Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WyomingView further author information
,
Lars Forslofb Roadroid, Ljusdal, SwedenView further author information
&
Khaled Ksaibatia Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WyomingORCID Iconhttps://orcid.org/0000-0002-9241-1792View further author information
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Pages 3797-3808 | Received 29 Aug 2020, Accepted 19 Apr 2021, Published online: 06 May 2021

Citations (5)

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Read on this site (1)

Nausheen Saeed, Roger G. Nyberg & Moudud Alam. (2022) Gravel road classification based on loose gravel using transfer learning. International Journal of Pavement Engineering 0:0, pages 1-8.
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Articles from other publishers (4)

Laura Ibagón, Bernardo Caicedo, Juan P. Villacreses & Fabricio Yepez. (2023) Modelling of Washboard Effect on Unpaved Roads Experimental Evidence on Non-cohesive Materials. Transportation Geotechnics, pages 101015.
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Osama Abu Daoud & Khaled Ksaibati. (2021) Studying the Effect of Gravel Roads Geometric Features on Corrugation Behavior. International Journal of Pavement Research and Technology 16:1, pages 44-52.
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Omar Albatayneh, Dima Husein, Ahmed Farid & Khaled Ksaibati. (2021) A Developed Methodology for Determining Gravel Roads’ Level of Service: A Case Study of Wyoming. International Journal of Pavement Research and Technology 15:4, pages 779-788.
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Osama Abu Daoud & Khaled Ksaibati. (2022) Artificial neural network-based roughness prediction models for gravel roads considering land use. Innovative Infrastructure Solutions 7:3.
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