Self-supervised learning with deep clustering for target detection in hyperspectral images with insufficient spectral variation prior-Reference-Cited by-同舟云学术

Self-supervised learning with deep clustering for target detection in hyperspectral images with insufficient spectral variation prior

Published:2023-08 Issue: Volume:122 Page:103405
ISSN:1569-8432
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Zhang Xiaodian^ORCID,Gao Kun,Wang Junwei,Hu Zibo,Wang Hong,Wang Pengyu^ORCID,Zhao Xiaobin,Li Wei

Funder

National Natural Science Foundation of China

Natural Science Foundation of Beijing Municipality

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference53 articles.

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3. Deep clustering for unsupervised learning of visual features;Caron,2018

5. Hyperspectral target detection: Hypothesis testing, signal-to-noise ratio, and spectral angle theories;Chang;IEEE Trans. Geosci. Remote Sens.,2021

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