Uncertainty-Aware Graph Self-Supervised Learning for Hyperspectral Image Change Detection-Reference-Cited by-同舟云学术

Uncertainty-Aware Graph Self-Supervised Learning for Hyperspectral Image Change Detection

Published:2024 Issue: Volume:62 Page:1-19
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Jian Ping¹,Ou Yimin¹^ORCID,Chen Keming²^ORCID

Affiliation:

1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

2. Key Laboratory of Network Information System Technology (NIST), Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Funder

Foundation Program of Key Laboratory of Science and Technology on Complex Electronic System Simulation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10426758.pdf?arnumber=10426758

Reference72 articles.

1. Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art

2. Hyperspectral and LiDAR Data Classification Based on Structural Optimization Transmission

3. Binary Change Guided Hyperspectral Multiclass Change Detection

4. A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges

5. Methods and Challenges Using Multispectral and Hyperspectral Images for Practical Change Detection Applications

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