CTSFFNet: Cross-Temporal Symmetric Feature Fusion Network for Hyperspectral Image Change Detection-Reference-Cited by-同舟云学术

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CTSFFNet: Cross-Temporal Symmetric Feature Fusion Network for Hyperspectral Image Change Detection

Published:2024-07-07 Issue: Volume: Page:9416-9419
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Lu Xukun¹,Duan Puhong²,Deng Bin²,Xie Zhuojun¹,Kang Xudong²

Affiliation:

1. Hunan University,College of Electrical and Information Engineering,China

2. Hunan University,School of Robotics,China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Hunan Province

China Postdoctoral Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10641169.pdf?arnumber=10641169

Reference8 articles.

1. Multiscale Diff-Changed Feature Fusion Network for Hyperspectral Image Change Detection

2. A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain

3. Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and $k$-Means Clustering

4. The Regularized Iteratively Reweighted MAD Method for Change Detection in Multi- and Hyperspectral Data

5. Multiple support vector machines for land cover change detection: An application for mapping urban extensions

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