Enhanced deep learning network for accurate digital elevation model generation from LiDAR data

This paper presents a unique hierarchical deep network to tackle the task of identifying and filtering non-ground objects from point cloud data. This task is essential in the building of digital terrain models (DTMs). The proposed network is based on a deep encoder-decoder architecture and includes...

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Veröffentlicht in:	Automation in construction Jg. 167; S. 105708
Hauptverfasser:	Al-Fugara, A'kif, Almomani, Mohammad H., Zitar, Raed Abu, Alzahrani, Ahmed Ibrahim, Alwadain, Ayed, Abualigah, Laith
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2024 Elsevier
Schlagworte:	Computer Science Digital terrain model (DTM) Feature fusion Hierarchical deep network Object classification Performance evaluation Point cloud data Performance evaluation Hierarchical deep network Digital terrain model (DTM) Feature fusion Object classification Point cloud data
ISSN:	0926-5805
Online-Zugang:	Volltext
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