Contrastive Scene Change Representation Learning for High-Resolution Remote Sensing Scene Change Detection-Reference-Cited by-同舟云学术

Contrastive Scene Change Representation Learning for High-Resolution Remote Sensing Scene Change Detection

Published:2024 Issue: Volume:62 Page:1-18
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Wang Jue¹^ORCID,Zhong Yanfei²^ORCID,Zhang Liangpei²^ORCID

Affiliation:

1. National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing, Beijing Institute of Technology, Beijing, China

2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 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/ielx7/36/10354519/10458973.pdf?arnumber=10458973

Reference60 articles.

1. Change detection techniques

2. Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images

3. ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very-High-Resolution Remote Sensing Images

4. Remote Sensing Image Scene Classification: Benchmark and State of the Art

5. Multi-Temporal Scene Classification and Scene Change Detection With Correlation Based Fusion

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. WSMsFNet: Joint the Whole Supervision and Multiscale Fusion Network for Remote Sensing Image Change Detection;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024