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Deep learning for estimating pavement roughness using synthetic aperture radar data

  • Published:2022-10 Issue: Volume:142 Page:104504
  • ISSN:0926-5805
  • Container-title:Automation in Construction
  • language:en
  • Short-container-title:Automation in Construction

Author:

Bashar Mohammad Z.,Torres-Machi Cristina

Funder

Minnesota Department of Transportation

Publisher

Elsevier BV

Subject

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

Reference43 articles.

1. Report Card for America’s Infrastructure, 2021;ASCE,2021

2. Highway Performance Monitoring System Field Manual;FHWA,2016

3. A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery;Shahi;Egypt. J. Remote Sens. Sp. Sci.,2015

4. Monitoring asphalt pavement damages using remote sensing techniques;Mettas,2015

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1. Quantifying knowledge: medical applications of radar aging through the lens of bibliometrics;Smart Biomedical and Physiological Sensor Technology XXI;2024-06-06

2. Smartphone-Based IRI Estimation for Pavement Roughness Monitoring: A Data-Driven Approach;IEEE Internet of Things Journal;2024-06-01

3. Evaluation of asphalt pavement texture using multiview stereo reconstruction based on deep learning;Construction and Building Materials;2024-01

4. UAV and SAT Images to Monitor Climate Conditions and Crop Yielding – a Survey;Lecture Notes in Networks and Systems;2024

5. Smart Road Damage Survey System Using Machine Vision and IoT Technology;2023 3rd International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA);2023-12-13
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