A New Learning Paradigm for Foundation Model-Based Remote-Sensing Change Detection-Reference-Cited by-同舟云学术

A New Learning Paradigm for Foundation Model-Based Remote-Sensing Change Detection

Published:2024 Issue: Volume:62 Page:1-12
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Li Kaiyu¹^ORCID,Cao Xiangyong¹^ORCID,Meng Deyu²^ORCID

Affiliation:

1. School of Computer Science and Technology and the Ministry of Education Key Laboratory for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, China

2. School of Mathematics and Statistics and the Ministry of Education Key Laboratory of Intelligent Networks and Network Security, Xi’an Jiaotong University, Shaanxi, Xi’an, China

Funder

National Key Research and Development Program of China

China NSFC Projects

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10438490.pdf?arnumber=10438490

Reference61 articles.

1. A Spatial-Temporal Attention-Based Method and a New Dataset for Remote Sensing Image Change Detection

2. Fully Convolutional Networks for Multisource Building Extraction From an Open Aerial and Satellite Imagery Data Set

3. SpaceNet 8 - The Detection of Flooded Roads and Buildings

4. A CNN-Transformer Network With Multiscale Context Aggregation for Fine-Grained Cropland Change Detection

5. Automatic analysis of the difference image for unsupervised change detection

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