A Multimodal Feature Fusion Network for Building Extraction With Very High-Resolution Remote Sensing Image and LiDAR Data-Reference-Cited by-同舟云学术

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A Multimodal Feature Fusion Network for Building Extraction With Very High-Resolution Remote Sensing Image and LiDAR Data

Published:2024 Issue: Volume:62 Page:1-19
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Luo Hui¹^ORCID,Feng Xibo¹,Du Bo²^ORCID,Zhang Yuxiang³^ORCID

Affiliation:

1. School of Computer Science, China University of Geosciences, Wuhan, China

2. School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, and Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China

3. Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10522766.pdf?arnumber=10522766

Reference53 articles.

1. Aspirations and realities of polycentric development: Insights from multi-source data into the emerging urban form of Shanghai

2. A Featureless Approach to 3D Polyhedral Building Modeling from Aerial Images

3. Assessment of Convolutional Neural Network Architectures for Earthquake-Induced Building Damage Detection based on Pre- and Post-Event Orthophoto Images

4. Big Data in Natural Disaster Management: A Review

5. Seismic vulnerability assessment at urban scale using data mining and GIScience technology: application to Urumqi (China)

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