CONTEXTUAL CLUSTERING AND UNMIXING OF GEOSPATIAL DATA BASED ON GAUSSIAN MIXTURE MODELS AND MARKOV RANDOM FIELDS

Bulletin of informatics and cybernetics ◽

10.5109/21045 ◽

2009 ◽

Vol 41 ◽

pp. 39-49

Author(s):

Yoko Sawamura ◽

Shuji Kawaguchi ◽

Tomohiko Ozaki

Keyword(s):

Mixture Models ◽

Random Fields ◽

Markov Random Fields ◽

Gaussian Mixture Models ◽

Gaussian Mixture ◽

Geospatial Data ◽

Markov Random

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Contextual Unmixing of Geospatial Data based on Gaussian Mixture Models and Markov Random Fields

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2008.4779660 ◽

2008 ◽

Cited By ~ 4

Author(s):

R. Nishii ◽

Y. Sawamura ◽

A. Nakamoto ◽

S. Kawaguchi

Keyword(s):

Mixture Models ◽

Random Fields ◽

Markov Random Fields ◽

Gaussian Mixture Models ◽

Gaussian Mixture ◽

Geospatial Data ◽

Markov Random

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A labeling scheme based on Markov Random Fields and Gaussian mixture models for hyperspectral images

2008 International Conference on Machine Learning and Cybernetics ◽

10.1109/icmlc.2008.4621033 ◽

2008 ◽

Author(s):

Xiu-Qin Huang ◽

Zhi-Wu Liao

Keyword(s):

Mixture Models ◽

Random Fields ◽

Markov Random Fields ◽

Gaussian Mixture Models ◽

Gaussian Mixture ◽

Hyperspectral Images ◽

Markov Random ◽

Labeling Scheme

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Hyperspectral Image Classification Using Gaussian Mixture Models and Markov Random Fields

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2013.2250905 ◽

2014 ◽

Vol 11 (1) ◽

pp. 153-157 ◽

Cited By ~ 90

Author(s):

Wei Li ◽

Saurabh Prasad ◽

James E. Fowler

Keyword(s):

Image Classification ◽

Mixture Models ◽

Random Fields ◽

Markov Random Fields ◽

Hyperspectral Image ◽

Gaussian Mixture Models ◽

Gaussian Mixture ◽

Hyperspectral Image Classification ◽

Markov Random

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Multi-subject connectivity-based parcellation of the human IPL using Gaussian mixture models and hidden Markov random fields

2013 IEEE 10th International Symposium on Biomedical Imaging ◽

10.1109/isbi.2013.6556526 ◽

2013 ◽

Cited By ~ 1

Author(s):

E Wang ◽

RF Tungaraza ◽

DR Haynor ◽

TJ Grabowski

Keyword(s):

Mixture Models ◽

Random Fields ◽

Markov Random Fields ◽

Hidden Markov ◽

Gaussian Mixture Models ◽

Gaussian Mixture ◽

Markov Random

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Reservoir Lithology Determination by Hidden Markov Random Fields Based on a Gaussian Mixture Model

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2018.2841059 ◽

2018 ◽

Vol 56 (11) ◽

pp. 6663-6673 ◽

Cited By ~ 7

Author(s):

Runhai Feng ◽

Stefan M. Luthi ◽

Dries Gisolf ◽

Erika Angerer

Keyword(s):

Gaussian Mixture Model ◽

Mixture Model ◽

Random Fields ◽

Markov Random Fields ◽

Hidden Markov ◽

Gaussian Mixture ◽

Markov Random

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Classification of very high resolution SAR images of urban areas by dictionary-based mixture models, copulas, and Markov random fields using textural features

10.1117/12.865023 ◽

2010 ◽

Cited By ~ 1

Author(s):

Aurélie Voisin ◽

Gabriele Moser ◽

Vladimir A. Krylov ◽

Sebastiano B. Serpico ◽

Josiane Zerubia

Keyword(s):

High Resolution ◽

Mixture Models ◽

Random Fields ◽

Urban Areas ◽

Markov Random Fields ◽

Textural Features ◽

Sar Images ◽

Markov Random ◽

Very High

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Sequential Gaussian Mixture Models for Two-Level Conditional Random Fields

Lecture Notes in Computer Science - Pattern Recognition ◽

10.1007/978-3-642-40602-7_16 ◽

2013 ◽

pp. 153-163 ◽

Cited By ~ 4

Author(s):

Sergey Kosov ◽

Franz Rottensteiner ◽

Christian Heipke

Keyword(s):

Mixture Models ◽

Random Fields ◽

Conditional Random Fields ◽

Gaussian Mixture Models ◽

Gaussian Mixture

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PET image segmentation using a Gaussian mixture model and Markov random fields

EJNMMI Physics ◽

10.1186/s40658-015-0110-7 ◽

2015 ◽

Vol 2 (1) ◽

Cited By ~ 13

Author(s):

Thomas Layer ◽

Matthias Blaickner ◽

Barbara Knäusl ◽

Dietmar Georg ◽

Johannes Neuwirth ◽

...

Keyword(s):

Image Segmentation ◽

Gaussian Mixture Model ◽

Mixture Model ◽

Random Fields ◽

Markov Random Fields ◽

Gaussian Mixture ◽

Markov Random

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Detecting and Tracking Unknown Number of Objects with Dirichlet Process Mixture Models and Markov Random Fields

Advances in Visual Computing - Lecture Notes in Computer Science ◽

10.1007/978-3-642-41939-3_18 ◽

2013 ◽

pp. 178-188

Author(s):

Ibrahim Saygin Topkaya ◽

Hakan Erdogan ◽

Fatih Porikli

Keyword(s):

Mixture Models ◽

Random Fields ◽

Dirichlet Process ◽

Markov Random Fields ◽

Dirichlet Process Mixture ◽

Unknown Number ◽

Markov Random ◽

Dirichlet Process Mixture Models

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Texture Segmentation of Urinary Sediment Image based on a Weighted Gaussian Mixture Model with Markov Random Fields

Proceedings of the 2018 7th International Conference on Bioinformatics and Biomedical Science - ICBBS '18 ◽

10.1145/3239264.3239276 ◽

2018 ◽

Cited By ~ 1

Author(s):

Xiaoming Jiang ◽

Fuqu Chen ◽

Qianqian Chen ◽

Miaomiao Si ◽

Wei Wang

Keyword(s):

Gaussian Mixture Model ◽

Mixture Model ◽

Random Fields ◽

Markov Random Fields ◽

Gaussian Mixture ◽

Texture Segmentation ◽

Urinary Sediment ◽

Markov Random

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