Multibranch Joint Representation Learning Based on Information Fusion Strategy for Cross-View Geo-Localization-Reference-Cited by-同舟云学术

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Multibranch Joint Representation Learning Based on Information Fusion Strategy for Cross-View Geo-Localization

Published:2024 Issue: Volume:62 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Ge Fawei¹^ORCID,Zhang Yunzhou¹^ORCID,Liu Yixiu²,Wang Guiyuan³,Coleman Sonya⁴^ORCID,Kerr Dermot⁴^ORCID,Wang Li¹

Affiliation:

1. College of Information Science and Engineering, Northeastern University, Shenyang, China

2. School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China

3. Jiangsu Shuguang Opto-Electronics Company Ltd., Yangzhou, China

4. Intelligent Systems Research Center, Ulster University, Londonderry, U.K

Funder

National Natural Science Foundation of China

Major Science and Technology Projects of Liaoning Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10473752.pdf?arnumber=10473752

Reference59 articles.

1. Each Part Matters: Local Patterns Facilitate Cross-View Geo-Localization

2. Novel Piecewise Distance Based on Adaptive Region Key-Points Extraction for LCCD With VHR Remote-Sensing Images

3. Land Cover Change Detection With Heterogeneous Remote Sensing Images: Review, Progress, and Perspective

4. Learning Representations From Skeletal Self-Similarities for Cross-View Action Recognition

5. Multiscale Attention Network Guided With Change Gradient Image for Land Cover Change Detection Using Remote Sensing Images

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