Eliminating Spatial Correlations of Anomaly: Corner-Visible Network for Unsupervised Hyperspectral Anomaly Detection
Author:
Affiliation:
1. Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum, Qingdao, China
2. College of Oceanography and Space Informatics, China University of Petroleum, Qingdao, China
Funder
National Natural Science Foundation of China
Joint Funds of the National Natural Science Foundation of China
Shandong Provincial Natural Science Foundation, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10296873.pdf?arnumber=10296873
Reference51 articles.
1. Hyperspectral Anomaly Detection With Multiscale Attribute and Edge-Preserving Filters
2. Hyperspectral Anomaly Detection Using Combined Similarity Criteria
3. Graph-Feature-Enhanced Selective Assignment Network for Hyperspectral and Multispectral Data Classification
4. Change Detection From Synthetic Aperture Radar Images via Graph-Based Knowledge Supplement Network
5. Collaborative Representation for Hyperspectral Anomaly Detection
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