Deep Feature Reconstruction Learning for Open-Set Classification of Remote-Sensing Imagery-Reference-Cited by-同舟云学术

Deep Feature Reconstruction Learning for Open-Set Classification of Remote-Sensing Imagery

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Sun Hao¹^ORCID,Li Qianqian²,Yu Jie³^ORCID,Zhou Dongbo²^ORCID,Chen Wenjing⁴^ORCID,Zheng Xiangtao⁵^ORCID,Lu Xiaoqiang⁵^ORCID

Affiliation:

1. Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, the School of Computer, and the National Language Resources Monitoring and Research Center for Network Media, Central China Normal University, Wuhan, China

2. Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, China

3. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

4. School of Computer Science, Hubei University of Technology, Wuhan, China

5. College of Physics and Information Engineering, Fuzhou University, Fuzhou, China

Funder

National Natural Science Foundation of China

Hubei Provincial Natural Science Foundation of China

National Science Fund for Distinguished Young Scholars

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10184907.pdf?arnumber=10184907

Reference18 articles.

1. Deep Residual Learning for Image Recognition

2. Classification-Reconstruction Learning for Open-Set Recognition

3. Conditional Gaussian Distribution Learning for Open Set Recognition

4. Towards Open Set Deep Networks

5. Few-Shot Hyperspectral Image Classification With Unknown Classes Using Multitask Deep Learning

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