DRFL-VAT: Deep Representative Feature Learning With Virtual Adversarial Training for Semisupervised Classification of Hyperspectral Image-Reference-Cited by-同舟云学术

DRFL-VAT: Deep Representative Feature Learning With Virtual Adversarial Training for Semisupervised Classification of Hyperspectral Image

Author:

Chen Jialong¹,Wang Yuebin¹^ORCID,Zhang Liqiang²^ORCID,Liu Meiling³^ORCID,Plaza Antonio⁴^ORCID

Affiliation:

1. School of Land Science and Technology, China University of Geosciences, Beijing, China

2. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China

3. School of Information and Engineering, China University of Geosciences, Beijing, China

4. Department of Computer Technology and Communications, Hyperspectral Computing Laboratory, University of Extremadura, Cáceres, Spain

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Key Research and Development Projects of Shanxi Province

Guizhou Science and Technology Plan Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference53 articles.

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