An encoder-decoder deep learning method for multi-class object segmentation from 3D tunnel point clouds

Discovering seepage is widely thought to be critical for maintaining the healthy conditions of the tunnel. Unfortunately, most of the seepage surveys are still manual with tedious, time-consuming, and inefficient as well as work-related physical injuries. To address this problem, this research propo...

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Veröffentlicht in:	Automation in construction Jg. 137; S. 104187
Hauptverfasser:	Ji, Ankang, Chew, Alvin Wei Ze, Xue, Xiaolong, Zhang, Limao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.05.2022 Elsevier BV
Schlagworte:	3D tunnel point-clouds Coders Data processing Deep learning Encoder-decoder Encoders-Decoders Feature extraction Image segmentation Machine learning Multi-class object segmentation Seepage Segmentation Teaching methods Three dimensional models Tunnels Deep learning 3D tunnel point-clouds Multi-class object segmentation Segmentation Encoder-decoder
ISSN:	0926-5805, 1872-7891
Online-Zugang:	Volltext
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