Parallel Compared-and-Stacked Pyramid Transformer Network for Unsupervised Hyperspectral Change Detection-Reference-Cited by-同舟云学术

Parallel Compared-and-Stacked Pyramid Transformer Network for Unsupervised Hyperspectral Change Detection

Published:2024 Issue: Volume:62 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Xu Yunshuang¹^ORCID,Xiao Song²,Qu Jiahui¹^ORCID,Dong Wenqian¹^ORCID,Li Yunsong¹^ORCID,Xia Haoming³^ORCID

Affiliation:

1. State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an, China

2. Beijing Electronic Science and Technology Institute, Beijing, China

3. College of Geography and Environmental Science and the Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Zhengzhou, China

Funder

China Postdoctoral Science Special Foundation

Young Talent Fund of Association for Science and Technology in Shaanxi

Fundamental Research Funds for the Central Universities

Young Talent Fund of Xi’an Association for Science and Technology

National Natural Science Foundation of China

Youth Innovation Team of Shaanxi Universities

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10361832.pdf?arnumber=10361832

Reference46 articles.

1. The Disaster Risk, Global Change, and Sustainability Nexus

2. CLNet: Cross-layer convolutional neural network for change detection in optical remote sensing imagery

3. BS³LNet: A New Blind-Spot Self-Supervised Learning Network for Hyperspectral Anomaly Detection

4. A Dual-Branch Detail Extraction Network for Hyperspectral Pansharpening

5. Asymmetric Weighted Logistic Metric Learning for Hyperspectral Target Detection

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