Towards Urban Scene Semantic Segmentation with Deep Learning from LiDAR Point Clouds: A Case Study in Baden-Württemberg, Germany

Towards Urban Scene Semantic Segmentation with Deep Learning from LiDAR Point Clouds: A Case Study in Baden-Württemberg, Germany

An accurate understanding of urban objects is critical for urban modeling, intelligent infrastructure planning and city management. The semantic segmentation of light detection and ranging (LiDAR) point clouds is a fundamental approach for urban scene analysis. Over the last years, several methods h...

Full description

Bibliographic Details
Main Authors: Yanling Zou, Holger Weinacker, Barbara Koch
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Remote Sensing
Subjects:
urban scene
mobile mapping
deep learning
remote sensing
point clouds
semantic segmentation
Online Access:https://www.mdpi.com/2072-4292/13/16/3220

Internet

https://www.mdpi.com/2072-4292/13/16/3220

Similar Items