Deep Learning Approach For Classification of Water Bottom and Surface from Bathymetric Lidar Point Clouds
Author:
Affiliation:
1. Kyungpook National University,Department of Location-Based Information System,Sangju,Republic of Korea
2. Konkuk University,Social Eco-Tech Institute,Seoul,Republic of Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10641485.pdf?arnumber=10641485
Reference5 articles.
1. Semantic Segmentation of Coastal Zone on Airborne Lidar Bathymetry Point Clouds
2. Extracting Shallow-Water Bathymetry from Lidar Point Clouds Using Pulse Attribute Data: Merging Density-Based and Machine Learning Approaches
3. Nearshore Bathymetry from ICESat-2 LiDAR and Sentinel-2 Imagery Datasets Using Deep Learning Approach
4. Water Bottom and Surface Classification Algorithm for Bathymetric LiDAR Point Clouds of Very Shallow Waters
5. Pointnet: Deep Learning on Point Sets for 3d Classification And Segmentation;Qi
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