Deep learning for large-scale point cloud segmentation in tunnels considering causal inference-Reference-Cited by-同舟云学术

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Deep learning for large-scale point cloud segmentation in tunnels considering causal inference

Published:2023-08 Issue: Volume:152 Page:104915
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Zhang Zhaoxiang,Ji Ankang,Zhang Limao,Xu Yuelei,Zhou Qing

Funder

Hebei Province Outstanding Youth Fund

National Natural Science Foundation of China

Huazhong University of Science and Technology

Publisher

Elsevier BV

Subject

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

Reference58 articles.

1. Metro systems and urban development: impacts and implications;Lin;Tunn. Undergr. Space Technol.,2022

2. Numerical study on the flow characteristics and smoke temperature evolution under double fires condition with a metro train in tunnel;Ren;Tunn. Undergr. Space Technol.,2021

3. Global sensitivity analysis of tunnel-induced building movements by a precise metamodel;Liu;J. Comput. Civ. Eng.,2017

4. Intelligent approach to estimation of tunnel-induced ground settlement using wavelet packet and support vector machines;Zhang;J. Comput. Civ. Eng.,2017

5. A tunnel information modelling framework to support management, simulations and visualisations in mechanised tunnelling projects;Koch;Autom. Constr.,2017

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4. Automated geometric quality inspection for modular boxes using BIM and LiDAR;Automation in Construction;2024-08

5. A Point Cloud Segmentation Method for Dim and Cluttered Underground Tunnel Scenes Based on the Segment Anything Model;Remote Sensing;2023-12-25

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