相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Masked Autoencoders for Point Cloud Self-supervised Learning
Yatian Pang et al.
COMPUTER VISION - ECCV 2022, PT II (2022)
Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data
Caileigh Shoot et al.
REMOTE SENSING (2021)
Tree species classification of LiDAR data based on 3D deep learning
Maohua Liu et al.
MEASUREMENT (2021)
PCT: Point cloud transformer
Meng-Hao Guo et al.
COMPUTATIONAL VISUAL MEDIA (2021)
Point Transformer
Nico Engel et al.
IEEE ACCESS (2021)
Comparative performance of convolutional neural network, weighted and conventional support vector machine and random forest for classifying tree species using hyperspectral and photogrammetric data
C. Sothe et al.
GISCIENCE & REMOTE SENSING (2020)
See the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning
Zhouxin Xi et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)
Urban Tree Species Classification Using a WorldView-2/3 and LiDAR Data Fusion Approach and Deep Learning
Sean Hartling et al.
SENSORS (2019)
Deep Learning Approaches for the Mapping of Tree Species Diversity in a Tropical Wetland Using Airborne LiDAR and High-Spatial-Resolution Remote Sensing Images
Ying Sun et al.
FORESTS (2019)
Object-Based Mangrove Species Classification Using Unmanned Aerial Vehicle Hyperspectral Images and Digital Surface Models
Jingjing Cao et al.
REMOTE SENSING (2018)
Mapping urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data
Luxia Liu et al.
REMOTE SENSING OF ENVIRONMENT (2017)
Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR
Benjamin Brede et al.
SENSORS (2017)
Random forest in remote sensing: A review of applications and future directions
Mariana Belgiu et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2016)
Bottom-up delineation of individual trees from full-waveform airborne laser scans in a structurally complex eucalypt forest
Iurii Shendryk et al.
REMOTE SENSING OF ENVIRONMENT (2016)
Combining Tandem-X InSAR and simulated GEDI lidar observations for forest structure mapping
Wenlu Qi et al.
REMOTE SENSING OF ENVIRONMENT (2016)
An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation
Wuming Zhang et al.
REMOTE SENSING (2016)
A bottom-up approach to segment individual deciduous trees using leaf-off lidar point cloud data
Xingcheng Lu et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2014)
Urban tree species mapping using hyperspectral and lidar data fusion
Michael Alonzo et al.
REMOTE SENSING OF ENVIRONMENT (2014)
Classification of tree species based on structural features derived from high density LiDAR data
Jili Li et al.
AGRICULTURAL AND FOREST METEOROLOGY (2013)
Lidar sampling for large-area forest characterization: A review
Michael A. Wulder et al.
REMOTE SENSING OF ENVIRONMENT (2012)
Using remotely sensed data to construct and assess forest attribute maps and related spatial products
Ronald E. McRoberts et al.
SCANDINAVIAN JOURNAL OF FOREST RESEARCH (2010)
Tree species differentiation using intensity data derived from leaf-on and leaf-off airborne laser scanner data
Sooyoung Kim et al.
REMOTE SENSING OF ENVIRONMENT (2009)
Laser scanning of forest resources: The Nordic experience
E Naesset et al.
SCANDINAVIAN JOURNAL OF FOREST RESEARCH (2004)
Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America
T Brandtberg et al.
REMOTE SENSING OF ENVIRONMENT (2003)