Anomaly detection based on quadratic modeling of hyperspectral imagery

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) ◽

10.1109/igarss.2016.7730532 ◽

2016 ◽

Author(s):

Shengwei Zhong ◽

Ye Zhang

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery

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Anomaly Detection for Hyperspectral Imagery Based on Incremental Support Vector Data Description

2010 International Conference on Multimedia Technology ◽

10.1109/icmult.2010.5631355 ◽

2010 ◽

Author(s):

Liyan Zhang ◽

Yonghua Sun ◽

Dan Meng ◽

Xiaojuan Li

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery ◽

Support Vector ◽

Support Vector Data Description ◽

Vector Data ◽

Data Description

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Real-time causal processing of anomaly detection for hyperspectral imagery

IEEE Transactions on Aerospace and Electronic Systems ◽

10.1109/taes.2014.130065 ◽

2014 ◽

Vol 50 (2) ◽

pp. 1511-1534 ◽

Author(s):

Shih-Yu Chen ◽

Yulei Wang ◽

Chao-Cheng Wu ◽

Chunhong Liu ◽

Chein-I Chang

Keyword(s):

Anomaly Detection ◽

Real Time ◽

Hyperspectral Imagery

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Anomaly detection from hyperspectral imagery

IEEE Signal Processing Magazine ◽

10.1109/79.974730 ◽

2002 ◽

Vol 19 (1) ◽

pp. 58-69 ◽

Author(s):

D.W.J. Stein ◽

S.G. Beaven ◽

L.E. Hoff ◽

E.M. Winter ◽

A.P. Schaum ◽

...

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery

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Kernel Eigenspace Separation Transform for Subspace Anomaly Detection in Hyperspectral Imagery

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2007.903083 ◽

2007 ◽

Vol 4 (4) ◽

pp. 581-585 ◽

Author(s):

H. Goldberg ◽

H. Kwon ◽

N. M. Nasrabadi

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery

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Anomaly Detection with Training Data in Hyperspectral Imagery

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp40776.2020.9053848 ◽

2020 ◽

Author(s):

Jun Liu ◽

Yutong Feng ◽

Weijian Liu ◽

Danilo Orlando ◽

Hongbin Li

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery ◽

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Topological Learning for Semi-Supervised Anomaly Detection in Hyperspectral Imagery

2019 IEEE National Aerospace and Electronics Conference (NAECON) ◽

10.1109/naecon46414.2019.9058127 ◽

2019 ◽

Author(s):

Juan Ramirez ◽

Tristan Armitage ◽

Trevor Bihl ◽

Ryan Kramer

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery

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A graph theoretic approach to anomaly detection in hyperspectral imagery

2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) ◽

10.1109/whispers.2011.6080899 ◽

2011 ◽

Author(s):

D. W. Messinger ◽

J. Albano

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery ◽

Theoretic Approach ◽

Graph Theoretic ◽

Graph Theoretic Approach

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Using self-organizing maps for anomaly detection in hyperspectral imagery

Proceedings, IEEE Aerospace Conference ◽

10.1109/aero.2002.1035291 ◽

2003 ◽

Author(s):

B.S. Penn

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery ◽

Self Organizing Maps ◽

Self Organizing

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An anomaly detection algorithm for hyperspectral imagery based on graph Laplacian

AOPC 2020: Optical Spectroscopy and Imaging; and Biomedical Optics ◽

10.1117/12.2575009 ◽

2020 ◽

Author(s):

Yuquan Gan ◽

Ying Liu ◽

Fanchao Yang

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery ◽

Graph Laplacian ◽

Detection Algorithm

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Anomaly detection in hyperspectral imagery

10.1117/12.428250 ◽

2001 ◽

Author(s):

Chein-I Chang ◽

Shao-Shan Chiang ◽

Irving W. Ginsberg

Keyword(s):

Anomaly Detection ◽

Hyperspectral Imagery

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