Building change detection in airborne laser scanning and dense image matching point clouds using a residual neural network

HIGHLIGHTS

• who: F. Politz and collaborators from the XXIV ISPRS Congress (, edition), June, Nice, France have published the paper: BUILDING CHANGE DETECTION IN AIRBORNE LASER SCANNING AND DENSE IMAGE MATCHING POINT CLOUDS USING A RESIDUAL NEURAL NETWORK, in the Journal: (JOURNAL)
• what: In the experiments the authors show that this approach is capable of detecting building changes automatically and reliably independent of the given point clouds and for various building sizes achieving mean F1 -Scores of 80.5% and 79.8% for ALS-ALS and ALS-DIM point clouds on an object-level and F1 -Scores . . .
  

   

  

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