Adaptively unsupervised seepage detection in tunnels from 3D point clouds-Reference-Cited by-同舟云学术

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Adaptively unsupervised seepage detection in tunnels from 3D point clouds

Published:2022-11-03 Issue: Volume: Page:1-19
ISSN:1573-2479
Container-title:Structure and Infrastructure Engineering
language:en
Short-container-title:Structure and Infrastructure Engineering

Author:

Wang Kunyu¹,Wu Xianguo¹,Li Heng²^ORCID,Wang Fan¹,Zhang Limao¹,Chen Hongyu³

Affiliation:

1. School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, Hubei, China

2. Department of Building and Real Estate, Hong Kong Polytechnic University, Kowloon, Hong Kong

3. School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore

Funder

The Ministry of Education Tier 1 Grants, Singapore

the Start-Up Grant at Nanyang Technological University, Singapore

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Ocean Engineering,Geotechnical Engineering and Engineering Geology,Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15732479.2022.2136718

Reference51 articles.

1. Cuttlefish Algorithm-Based Multilevel 3-D Otsu Function for Color Image Segmentation

2. Adapted Delaunay triangulation method for free-form surface generation from random point clouds for stochastic optimization applications

3. A New Iterative Triclass Thresholding Technique in Image Segmentation

4. Feature Selection and Non-Linear Classifiers: Effects on Simultaneous Motion Recognition in Upper Limb

5. Behavior-based safety on construction sites: A case study

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