Large-Scale ALS Point Cloud Segmentation via Projection-Based Context Embedding-Reference-Cited by-同舟云学术

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Large-Scale ALS Point Cloud Segmentation via Projection-Based Context Embedding

Published:2024 Issue: Volume:62 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Dai Hengming¹^ORCID,Hu Xiangyun²^ORCID,Zhang Jinming³^ORCID,Shu Zhen¹^ORCID,Xu Jiabo¹,Du Juan¹^ORCID

Affiliation:

1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

2. School of Remote Sensing and Information Engineering, Hubei Luojia Laboratory, Institute of Artificial Intelligence in Geomatics, Wuhan University, Wuhan, China

3. Key Laboratory of Network Information System Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing, China

Funder

Special Fund of Hubei Luojia Laboratory

Fundamental Research Funds for the Central Universities, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10506699.pdf?arnumber=10506699

Reference62 articles.

1. Semantic supported urban change detection using ALS point clouds

2. Large-scale estimation of change in aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data

3. Automated Reconstruction of Building LoDs from Airborne LiDAR Point Clouds Using an Improved Morphological Scale Space

4. OpenGF: An Ultra-Large-Scale Ground Filtering Dataset Built Upon Open ALS Point Clouds Around the World

5. Feature relevance assessment for the semantic interpretation of 3D point cloud data

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