A point cloud segmentation method for power lines and towers based on a combination of multiscale density features and point-based deep learning-Reference-Cited by-同舟云学术

A point cloud segmentation method for power lines and towers based on a combination of multiscale density features and point-based deep learning

Published:2023-03 Issue:1 Volume:16 Page:620-644
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Zhao Wenbo¹²³,Dong Qing¹²⁴,Zuo Zhengli¹

Affiliation:

1. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of China

2. International Research Center of Big Data for Sustainable Development Goals, Beijing, People’s Republic of China

3. University of Chinese Academy of Sciences, Beijing, People’s Republic of China

4. Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Zhejiang, People’s Republic of China

Funder

Chengdu University of Technology Postgraduate Innovative Cultivation Program

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2168770

Reference50 articles.

1. Quantitative prediction and evaluation of geothermal resource areas in the southwest section of the Mid-Spine Belt of Beautiful China

2. 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks

3. Alternative k-nearest neighbour rules in supervised pattern recognition

4. Power line detection from synthetic aperture radar imagery using coherence of co-polarisation and cross-polarisation estimated in the Hough domain

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