Learning Disentangled Priors for Hyperspectral Anomaly Detection: A Coupling Model-Driven and Data-Driven Paradigm-Reference-Cited by-同舟云学术

Learning Disentangled Priors for Hyperspectral Anomaly Detection: A Coupling Model-Driven and Data-Driven Paradigm

Published:2024 Issue: Volume: Page:1-14
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Li Chenyu¹^ORCID,Zhang Bing¹^ORCID,Hong Danfeng¹^ORCID,Jia Xiuping²^ORCID,Plaza Antonio³^ORCID,Chanussot Jocelyn¹^ORCID

Affiliation:

1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

2. School of Engineering and Information Technology, The University of New South Wales, Canberra, ACT, Australia

3. Department of Technology of Computers and Communications, Escuela Politécnica, Hyperspectral Computing Laboratory, University of Extremadura, Cáceres, Spain

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/ielx8/5962385/6104215/10547283.pdf?arnumber=10547283

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