Hierarchical Attention Feature Fusion-Based Network for Land Cover Change Detection With Homogeneous and Heterogeneous Remote Sensing Images-Reference-Cited by-同舟云学术

Hierarchical Attention Feature Fusion-Based Network for Land Cover Change Detection With Homogeneous and Heterogeneous Remote Sensing Images

Published:2023 Issue: Volume:61 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Lv Zhiyong¹^ORCID,Liu Jie¹,Sun Weiwei²^ORCID,Lei Tao³^ORCID,Benediktsson Jón Atli⁴^ORCID,Jia Xiuping⁵^ORCID

Affiliation:

1. School of Computer Science and Engineering; Shaanxi Key Laboratory of Network Computing and Security Technology, Xi’an University of Technology, Xi’an, Shaanxi, China

2. Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, Zhejiang, China

3. School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China

4. Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland

5. School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia

Funder

National Natural Science Foundations of China

Natural Science Basic Research Programs of Shaanxi

Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10330614.pdf?arnumber=10330614

Reference68 articles.

1. Change Detection Based on Artificial Intelligence: State-of-the-Art and Challenges

2. A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images

3. Change Detection From Very-High-Spatial-Resolution Optical Remote Sensing Images: Methods, applications, and future directions

4. Change Detection in Heterogeneous Optical and SAR Remote Sensing Images Via Deep Homogeneous Feature Fusion

5. A Survey on Deep Learning-Based Change Detection from High-Resolution Remote Sensing Images

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