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Ground material classification for UAV-based photogrammetric 3D data A 2D-3D Hybrid Approach
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Ground material classification for UAV-based photogrammetric 3D data A 2D-3D Hybrid Approach

Meida Chen
Andrew Feng
Yu Hou
Kyle McCullough
P. Prasad
L. Soibelman
ArXiv (abs)PDFHTML

Papers citing "Ground material classification for UAV-based photogrammetric 3D data A 2D-3D Hybrid Approach"

5 / 5 papers shown
Title
Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models
Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models
Meida Chen
Andrew Feng
Kyle McCullough
P. Prasad
R. McAlinden
L. Soibelman
3DPC
31
6
0
21 Aug 2020
Fully Automated Photogrammetric Data Segmentation and Object Information Extraction Approach for Creating Simulation Terrain
Fully Automated Photogrammetric Data Segmentation and Object Information Extraction Approach for Creating Simulation Terrain
Meida Chen
Andrew Feng
Kyle McCullough
P. Prasad
R. McAlinden
L. Soibelman
M. Enloe
35
10
0
09 Aug 2020
3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation
3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation
Angela Dai
Matthias Nießner
3DPC3DV
46
324
0
28 Mar 2018
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Adam Paszke
Abhishek Chaurasia
Sangpil Kim
Eugenio Culurciello
SSeg
324
2,084
0
07 Jun 2016
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAttSSL
595
15,902
0
12 Nov 2013

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