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Detecting Historical Terrain Anomalies With UAV-LiDAR Data Using Spline-Approximation and Support Vector Machines.
Marcel Storch
Norbert de Lange
Thomas Jarmer
Björn Waske
Published in:
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2023)
Keyphrases
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lidar data
support vector
aerial imagery
urban environments
point cloud
high resolution
anomaly detection
feature selection
three dimensional
path planning
urban areas
watershed segmentation
hyperspectral imagery
computer vision
support vectors
kernel function
multispectral