ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1702.06188
  4. Cited By
Forest understory trees can be segmented accurately within sufficiently
  dense airborne laser scanning point clouds
v1v2 (latest)

Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds

17 February 2017
Hamid Hamraz
M. Contreras
Jun Zhang
ArXiv (abs)PDFHTML

Papers citing "Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds"

4 / 4 papers shown
Title
Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans
Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans
E. Kalinicheva
Loic Landrieu
Clement Mallet
N. Chehata
3DPC3DV
61
8
0
25 Apr 2022
Three-dimensional Segmentation of Trees Through a Flexible Multi-Class
  Graph Cut Algorithm (MCGC)
Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC)
Jonathan Williams
Carola-Bibiane Schönlieb
T. Swinfield
Juheon Lee
Xiaohao Cai
L. Qie
David A. Coomes
3DPC
23
47
0
20 Mar 2019
Deep learning for conifer/deciduous classification of airborne LiDAR 3D
  point clouds representing individual trees
Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees
Hamid Hamraz
Nathan Jacobs
M. Contreras
Chase Clark
3DPC
71
102
0
24 Feb 2018
Vertical stratification of forest canopy for segmentation of under-story
  trees within small-footprint airborne LiDAR point clouds
Vertical stratification of forest canopy for segmentation of under-story trees within small-footprint airborne LiDAR point clouds
Hamid Hamraz
M. Contreras
Jun Zhang
3DPC
62
84
0
31 Dec 2016
1