3DGraphSeg: A Unified Graph Representation- Based Point Cloud Segmentation Framework for Full-Range High-Speed Railway Environments-Reference-Cited by-同舟云学术

3DGraphSeg: A Unified Graph Representation- Based Point Cloud Segmentation Framework for Full-Range High-Speed Railway Environments

Published:2023-12 Issue:12 Volume:19 Page:11430-11443
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Geng Yixuan¹^ORCID,Wang Zhipeng¹^ORCID,Jia Limin¹^ORCID,Qin Yong¹^ORCID,Chai Yuanyuan²,Liu Keyan¹,Tong Lei¹

Affiliation:

1. State Key Laboratory of Rail Traffic Control and Safety and the Key Laboratory of Railway Industry of Proactive Safety and Risk Control, Beijing Jiaotong University, Beijing, China

2. JIT Research Institute, Jilin University Zhengyuan Information Technologies Co., Ltd., Beijing, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Research Project of State Key Laboratory of Rail Traffic Control and Safety

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/10288179/10049148.pdf?arnumber=10049148

Reference37 articles.

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2. PointNet++: Deep hierarchical feature learning on point sets in a metric space;qi;Proc Adv Neural Inf Process Syst,0

3. LiDAR Point Cloud Recognition of Overhead Catenary System with Deep Learning

4. RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

5. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

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