Individual Tree Species Classification Using the Pointwise MLP-Based Point Cloud Deep Learning Method
Author:
Publisher
MDPI
Link
https://www.mdpi.com/2673-4931/22/1/19/pdf
Reference22 articles.
1. Tree species classification using structural features derived from terrestrial laser scanning;ISPRS J. Photogramm. Remote Sens.,2020
2. Automatic tree species recognition with quantitative structure models;Remote Sens. Environ.,2017
3. Riparian trees genera identification based on leaf-on/leaf-off airborne laser scanner data and machine learning classifiers in northern France;Int. J. Remote Sens.,2019
4. Tree species classification based on explicit tree structure feature parameters derived from static terrestrial laser scanning data;Agric. For. Meteorol.,2016
5. Identifying the genus or species of individual trees using a three-wavelength airborne lidar system;Remote Sens. Environ.,2018
Cited by 5 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. An Efficient Technique for Determining Tree Coordinates using LiDAR Data via Deep Learning;2024 6th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE);2024-02-29
2. Urban Tree Species Classification Using UAV-Based Multispectral Images and LiDAR Point Clouds;Journal of Geovisualization and Spatial Analysis;2023-12-13
3. Individual Tree Segmentation Quality Evaluation Using Deep Learning Models LiDAR Based;Optical Memory and Neural Networks;2023-11-28
4. Improved 3D point cloud segmentation for accurate phenotypic analysis of cabbage plants using deep learning and clustering algorithms;Computers and Electronics in Agriculture;2023-08
5. TSCMDL: Multimodal Deep Learning Framework for Classifying Tree Species Using Fusion of 2-D and 3-D Features;IEEE Transactions on Geoscience and Remote Sensing;2023
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3