A Knowledge-Based Multi-Scale Adaptive Classification Approach for Mobile Laser Scanning Point Clouds in Urban Scenes-Reference-Cited by-同舟云学术

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A Knowledge-Based Multi-Scale Adaptive Classification Approach for Mobile Laser Scanning Point Clouds in Urban Scenes

Published:2023 Issue: Volume:11 Page:134531-134546
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zheng Mingxue¹^ORCID,Shen Xiangcheng¹,Luo Zhiqing¹,Chen Pingting¹,Guan Bo¹,Yi Jicheng¹,Ma Hairong¹^ORCID

Affiliation:

1. Institute of Agricultural Economy and Technology, Hubei Academy of Agricultural Sciences, Wuhan, China

Funder

National Natural Science Foundation of China

Youth Fund of Hubei Academy of Agricultural Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10325490.pdf?arnumber=10325490

Reference84 articles.

1. An Efficient and General Framework for Aerial Point Cloud Classification in Urban Scenarios

2. 3D fully convolutional network for vehicle detection in point cloud

3. Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data

4. Building extraction from oblique airborne imagery based on robust façade detection

5. Robust point cloud classification based on multi-level semantic relationships for urban scenes

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