Hyperspectral Anomaly Detection Using Quantum Potential Clustering-Reference-Cited by-同舟云学术

Hyperspectral Anomaly Detection Using Quantum Potential Clustering

Published:2022 Issue: Volume:71 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Tu Bing¹^ORCID,Wang Zhi¹^ORCID,Yang Xianchang¹^ORCID,Li Jun²^ORCID,Plaza Antonio³^ORCID

Affiliation:

1. School of Information Science and Technology, Hunan Institute of Science and Technology, Yueyang, China

2. School of Computer Science and the Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China

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

Funder

National Natural Science Foundation of China

Science Foundation for Distinguished Young Scholars of Hunan Province

Key Research and Development Program of Hunan Province

Foundation of Department of Water Resources of Hunan Province

Natural Science Foundation of Hunan Province

Foundation of Education Bureau of Hunan Province

Junta de Extremadura

Spanish Ministerio de Ciencia e Innovacion

European Union’s Horizon 2020 Research and Innovation Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09933907.pdf?arnumber=9933907

Reference49 articles.

1. Weakly Supervised Low-Rank Representation for Hyperspectral Anomaly Detection

2. Autoencoder and Adversarial-Learning-Based Semisupervised Background Estimation for Hyperspectral Anomaly Detection

3. Discriminative Reconstruction Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection

4. An Overview of Deep Learning Based Methods for Unsupervised and Semi-Supervised Anomaly Detection in Videos

5. Generative Adversarial Networks: An Overview

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