Semantic segmentation of airborne LiDAR point cloud based on global geometric attention network

Han Li; Chaoguang Men; Yongmei Liu

doi:10.1109/icedcs64328.2024.00061

ScienceGate Book Chapters

JOURNAL ARTICLE

Semantic segmentation of airborne LiDAR point cloud based on global geometric attention network

Han Li Chaoguang Men Yongmei Liu

Year: 2024 Pages: 309-313

DOI: 10.1109/icedcs64328.2024.00061

Get Full-Text PDF Get Analytical Report

Keywords:

Lidar Point cloud Segmentation Computer science Remote sensing Cloud computing Artificial intelligence Point (geometry) Computer vision Meteorology Geology Geography Geometry

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.24

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Remote Sensing and LiDAR Applications

Physical Sciences → Environmental Science → Environmental Engineering

3D Shape Modeling and Analysis

Physical Sciences → Engineering → Computational Mechanics

3D Surveying and Cultural Heritage

Physical Sciences → Earth and Planetary Sciences → Geology

Semantic segmentation of airborne LiDAR point cloud based on global geometric attention network

Metrics

Topics

Related Documents

Multilevel intuitive attention neural network for airborne LiDAR point cloud semantic segmentation

A Dual Attention Neural Network for Airborne LiDAR Point Cloud Semantic Segmentation

Semantic segmentation of airborne LiDAR point cloud based on multi-feature fusion and geometric convolution

Research on Semantic Segmentation of Airborne LiDAR Point Cloud Based on Spatial Position Attention Mechanism

GA-NET: Global Attention Network for Point Cloud Semantic Segmentation