Tree Species Classification of Point Clouds from Different Laser Sensors Using the PointNet++ Deep Learning Method

Author:

Liu Bingjie1,Huang Huaguo1,Chen Shuxin2,Tian Xin2,Ren Min3

Affiliation:

1. Beijing Forestry University,State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management,China

2. Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,China

3. China Mobile Group Shanxi Design Institute Co., Ltd.,China

Funder

Chinese Academy of Forestry

National Science and Technology Major Project

National Natural Science Foundation of China

Publisher

IEEE

Reference15 articles.

1. Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

2. Competitive drivers of interspecific deviations of crown morphology from theoretical predictions measured with Terrestrial Laser Scanning

3. PointNet++: Deep hierarchical feature learning on point sets in a metric space;qi;Proc Adv Neural Inf Process Syst,2017

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

5. Tree species classification from complex laser scanning data in Mediterranean forests using deep learning;allen;Methods Ecol Evol,2022

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing Tree Species Classification of Point Clouds via Resampling;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. Classify Tree Species from Point Clouds Generated by Different Laser Sensors: A Multi-View Projection Strategy;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

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