Learnable Background Endmember With Subspace Representation for Hyperspectral Anomaly Detection-Reference-Cited by-同舟云学术

Learnable Background Endmember With Subspace Representation for Hyperspectral Anomaly Detection

Author:

Guo Tan¹^ORCID,He Long¹,Luo Fulin²^ORCID,Gong Xiuwen³^ORCID,Zhang Lei⁴^ORCID,Gao Xinbo⁵^ORCID

Affiliation:

1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

2. College of Computer Science, Chongqing University, Chongqing, China

3. Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia

4. School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China

5. Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Chongqing

Key Scientific and Technological Innovation Project for ``Chengdu-Chongqing Double City Economic Circle''

Macao Young Scholars Program

Fundamental Research Funds for the Central Universities

Open Project of Center for Applied Mathematics of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference46 articles.

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