Airborne lidar point cloud classification using pointnet++ network with full neighborhood features

HIGHLIGHTS

• who: Xingzhong Nong et al. from the Wuhan University, Wuhan, China have published the article: Airborne LiDAR point cloud classification using PointNet++ network with full neighborhood features, in the Journal: PLOS ONE of 23/Dec/2022
• what: The authors propose a framework based on the PointNet++ network. The authors proposed an interpolation method that uses adaptive elevation weight to make full use of the objects in the airborne LiDAR point which exhibits discrepancies in elevation distributions. The authors proposed a network modified from the PointNet++ network according to ALS point cloud characteristic. The research shows . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.