Deep learning-based underground object detection for urban road pavement-Reference-Cited by-同舟云学术

Deep learning-based underground object detection for urban road pavement

Published:2018-12-20 Issue:13 Volume:21 Page:1638-1650
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Kim Namgyu¹,Kim Kideok¹,An Yun-Kyu²,Lee Hyun-Jong¹^ORCID,Lee Jong-Jae¹

Affiliation:

1. Department of Civil and Environmental Engineering, Sejong University, Seoul, Republic of Korea

2. Department of Architectural Engineering, Sejong University, Seoul, Republic of Korea

Funder

Ministry of Land, Infrastructure and Transport

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2018.1559317

Reference27 articles.

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2. Becker, J.T., 2014. Deep learning methods for multiband explosive hazard detection using L-band and X-band forward-looking ground-penetrating radar.

3. Boyle, D., 2017. Massive 20 ft sinkhole suddenly opens up in busy dual carriageway causing tra ! ic chaos for thousands. Dailymail [online]. Available from: http://www.dailymail.co.uk/news/article-4651474/Massive-20ft-sinkhole-suddenly-opens-Liverpool-road.html.

4. Real-Time Hyperbola Recognition and Fitting in GPR Data

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