A novel unsupervised classification approach for hyperspectral imagery based on spectral mixture model and MARKOV random field

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

10.1109/igarss.2016.7729632 ◽

2016 ◽

Author(s):

Yuan Fang ◽

Linlin Xu ◽

Xiao Sun ◽

Longshan Yang ◽

Yujia Chen ◽

...

Keyword(s):

Random Field ◽

Mixture Model ◽

Markov Random Field ◽

Hyperspectral Imagery ◽

Unsupervised Classification ◽

Classification Approach ◽

Markov Random ◽

Spectral Mixture

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Unsupervised Bayesian Subpixel Mapping of Hyperspectral Imagery Based on Band-Weighted Discrete Spectral Mixture Model and Markov Random Field

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2020.2967104 ◽

2021 ◽

Vol 18 (1) ◽

pp. 162-166

Author(s):

Yujia Chen ◽

Linlin Xu ◽

Yuan Fang ◽

Junhuan Peng ◽

Wenfu Yang ◽

...

Keyword(s):

Random Field ◽

Mixture Model ◽

Markov Random Field ◽

Hyperspectral Imagery ◽

Markov Random ◽

Subpixel Mapping ◽

Spectral Mixture

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Unsupervised Bayesian Classification of a Hyperspectral Image Based on the Spectral Mixture Model and Markov Random Field

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ◽

10.1109/jstars.2018.2858008 ◽

2018 ◽

Vol 11 (9) ◽

pp. 3325-3337 ◽

Author(s):

Yuan Fang ◽

Linlin Xu ◽

Junhuan Peng ◽

Honglei Yang ◽

Alexander Wong ◽

...

Keyword(s):

Random Field ◽

Mixture Model ◽

Markov Random Field ◽

Hyperspectral Image ◽

Bayesian Classification ◽

Markov Random ◽

Spectral Mixture

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MR brain imaging segmentation based on spatial Gaussian mixture model and Markov random field

IEEE International Conference on Image Processing 2005 ◽

10.1109/icip.2005.1529750 ◽

2005 ◽

Author(s):

Zhigang Peng ◽

W. Wee ◽

Jing-Huei Lee

Keyword(s):

Random Field ◽

Brain Imaging ◽

Gaussian Mixture Model ◽

Mixture Model ◽

Markov Random Field ◽

Gaussian Mixture ◽

Markov Random ◽

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Errata: Adaptive support vector machine and Markov random field model for classifying hyperspectral imagery

Journal of Applied Remote Sensing ◽

10.1117/1.3628662 ◽

2011 ◽

Vol 5 (1) ◽

pp. 050101

Author(s):

Shanshan Li

Keyword(s):

Support Vector Machine ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Hyperspectral Imagery ◽

Support Vector ◽

Random Field Model ◽

Markov Random Field Model ◽

Markov Random ◽

Adaptive Support

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Bayesian Classification of Hyperspectral Imagery Based on Probabilistic Sparse Representation and Markov Random Field

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2013.2279395 ◽

2014 ◽

Vol 11 (4) ◽

pp. 823-827 ◽

Author(s):

Linlin Xu ◽

Jonathan Li

Keyword(s):

Random Field ◽

Sparse Representation ◽

Markov Random Field ◽

Hyperspectral Imagery ◽

Bayesian Classification ◽

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A Mixture Model Based Markov Random Field for Discovering Patterns in Sequences

Advances in Artificial Intelligence - Lecture Notes in Computer Science ◽

10.1007/11752912_5 ◽

2006 ◽

pp. 25-34

Author(s):

Konstantinos Blekas

Keyword(s):

Random Field ◽

Mixture Model ◽

Markov Random Field ◽

Model Based ◽

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Improved Mixture Model for Markov Random Field and Its Application in Magnetic Resonance Image Segmentation

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2017.2060 ◽

2017 ◽

Vol 7 (2) ◽

pp. 323-329 ◽

Author(s):

Xiaolong Wang ◽

Shuang He ◽

Zhigang Tong

Keyword(s):

Image Segmentation ◽

Magnetic Resonance ◽

Random Field ◽

Mixture Model ◽

Markov Random Field ◽

Magnetic Resonance Image ◽

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Adaptive Markov Random Field Approach for Classification of Hyperspectral Imagery

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2011.2145353 ◽

2011 ◽

Vol 8 (5) ◽

pp. 973-977 ◽

Author(s):

Bing Zhang ◽

Shanshan Li ◽

Xiuping Jia ◽

Lianru Gao ◽

Man Peng

Keyword(s):

Random Field ◽

Markov Random Field ◽

Hyperspectral Imagery ◽

Field Approach ◽

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Gaussian Mixture Model with Markov Random Field for MR Image Segmentation

2006 IEEE International Conference on Industrial Technology ◽

10.1109/icit.2006.372426 ◽

2006 ◽

Author(s):

Huiguang He ◽

Ke Lu ◽

Bin Lv

Keyword(s):

Image Segmentation ◽

Random Field ◽

Gaussian Mixture Model ◽

Mixture Model ◽

Markov Random Field ◽

Gaussian Mixture ◽

Mr Image ◽

Markov Random ◽

Mr Image Segmentation

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Ground-Glass-Opacity Nodule Detection and Segmentation Based on Dot Filter and Gaussian Mixture Model Hidden Markov Random Field

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2014.1276 ◽

2014 ◽

Vol 4 (3) ◽

pp. 399-403 ◽

Author(s):

Shenshen Sun ◽

Huizhi Ren

Keyword(s):

Random Field ◽

Gaussian Mixture Model ◽

Mixture Model ◽

Markov Random Field ◽

Hidden Markov ◽

Ground Glass Opacity ◽

Gaussian Mixture ◽

Markov Random ◽

Nodule Detection ◽

Hidden Markov Random Field

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