Automatic detection of moisture damages in asphalt pavements from GPR data with deep CNN and IRS method-Reference-Cited by-同舟云学术

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Automatic detection of moisture damages in asphalt pavements from GPR data with deep CNN and IRS method

Published:2020-05 Issue: Volume:113 Page:103119
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Zhang Jun,Yang Xing,Li Weiguang,Zhang Shaobo,Jia Yunyi

Funder

National Natural Science Foundation of China

Highway Administration of Zhejiang Province

Scientific and Technological Project of Department of Transport of Shaanxi Province

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference28 articles.

1. Chemical and mechanical processes influencing adhesion and moisture damage in hot mix asphalt pavements;Little,2018

2. A review on moisture damages of hot and warm mix asphalt and related investigations;Kakar;J. Clean. Prod.,2015

3. The effect of using anti-stripping additives on moisture damage of hot mix asphalt;Hamedi;Int. J. Adhes. Adhes.,2018

4. Non-invasive estimation of moisture content in tuff bricks by GPR;Agliata;Constr. Build. Mater.,2018

5. Integrated GPR and laboratory water content measures of sandy soils: from laboratory to field scale;Ercoli;Constr. Build. Mater.,2018

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5. Comparison of Residual Network and Other Classical Models for Classification of Interlayer Distresses in Pavement;Applied Sciences;2024-07-27

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