Deep-Learning-Based Semantic Segmentation Approach for Point Clouds of Extra-High-Voltage Transmissi...
Deep-Learning-Based Semantic Segmentation Approach for Point Clouds of Extra-High-Voltage Transmission Lines
About this item
Full title
Author / Creator
Yu, Hao , Wang, Zhengyang , Zhou, Qingjie , Ma, Yuxuan , Wang, Zhuo , Liu, Huan , Ran, Chunqing , Wang, Shengli , Zhou, Xinghua and Zhang, Xiaobo
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
The accurate semantic segmentation of point cloud data is the basis for their application in the inspection of extra high-voltage transmission lines (EHVTL). As deep learning evolves, point-wise-based deep neural networks have shown great potential for the semantic segmentation of EHVTL point clouds. However, EHVTL point cloud data are characterize...
Alternative Titles
Full title
Deep-Learning-Based Semantic Segmentation Approach for Point Clouds of Extra-High-Voltage Transmission Lines
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_316def11ac9b483aaee94ffe0531ea1f
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_316def11ac9b483aaee94ffe0531ea1f
Other Identifiers
ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs15092371
