DHI-Net: A Novel Detail-Preserving and Hierarchical Interaction Network For Building Extraction-Reference-Cited by-同舟云学术

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DHI-Net: A Novel Detail-Preserving and Hierarchical Interaction Network For Building Extraction

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Song Baogui¹^ORCID,Shao Wen¹,Shao Pan¹^ORCID,Wang Jianming²,Xiong Jing¹,Qi Chenwei¹

Affiliation:

1. Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering, and the College of Computer and Information Technology, China Three Gorges University, Yichang, Hubei, China

2. Fujian Second Geological Exploration Brigade, Sanming, Fujian, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/8859/10365397/10623506.pdf?arnumber=10623506

Reference22 articles.

1. JointNet: A Common Neural Network for Road and Building Extraction

2. Multiscale Building Extraction With Refined Attention Pyramid Networks

3. Building Extraction From Very High-Resolution Remote Sensing Images Using Refine-UNet

4. AttentionBuildNet for Building Extraction from Aerial Imagery

5. CSA-UNet: Channel-Spatial Attention-Based Encoder–Decoder Network for Rural Blue-Roofed Building Extraction From UAV Imagery

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