ParSymG: a parallel clustering approach for unsupervised classification of remotely sensed imagery

International Journal of Digital Earth ◽

10.1080/17538947.2016.1229818 ◽

2016 ◽

Vol 10 (5) ◽

pp. 471-489 ◽

Author(s):

Zhenhong Du ◽

Yuhua Gu ◽

Chuanrong Zhang ◽

Feng Zhang ◽

Renyi Liu ◽

...

Keyword(s):

Unsupervised Classification ◽

Remotely Sensed ◽

Remotely Sensed Imagery ◽

Clustering Approach ◽

Parallel Clustering

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Contextual unsupervised classification of remotely sensed imagery with mixels

10.1117/12.689566 ◽

2006 ◽

Author(s):

Shuji Kawaguchi ◽

Ryuei Nishii

Keyword(s):

Unsupervised Classification ◽

Remotely Sensed ◽

Remotely Sensed Imagery

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Parameter Selection for Segmentation in Object-Oriented Classification of Remotely Sensed Imagery

2010 International Conference on Intelligent Computation Technology and Automation ◽

10.1109/icicta.2010.710 ◽

2010 ◽

Author(s):

Shukui Bo ◽

Xinchao Han

Keyword(s):

Object Oriented ◽

Remotely Sensed ◽

Parameter Selection ◽

Remotely Sensed Imagery ◽

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Supervised Classification of Remotely Sensed Imagery Using a Modified $k$-NN Technique

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2008.916629 ◽

2008 ◽

Vol 46 (7) ◽

pp. 2112-2125 ◽

Author(s):

L. Samaniego ◽

A. Bardossy ◽

K. Schulz

Keyword(s):

Supervised Classification ◽

Remotely Sensed ◽

Remotely Sensed Imagery

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Training strategies for neural network soft classification of remotely-sensed imagery

International Journal of Remote Sensing ◽

10.1080/014311697218160 ◽

1997 ◽

Vol 18 (8) ◽

pp. 1851-1856 ◽

Author(s):

A. C. Bernard ◽

G. G. Wilkinson ◽

I. Kanellopoulos

Keyword(s):

Neural Network ◽

Remotely Sensed ◽

Remotely Sensed Imagery ◽

Soft Classification ◽

Training Strategies

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Alpha-shapes for visualizing irregular-shaped class clusters in 3D feature space for classification of remotely sensed imagery

10.1117/12.539219 ◽

2004 ◽

Author(s):

Arko Lucieer ◽

Menno-Jan Kraak

Keyword(s):

Feature Space ◽

Remotely Sensed ◽

Remotely Sensed Imagery ◽

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ANN Classification of OMIS Hyperspectral Remotely Sensed Imagery: Experiments and Analysis

2008 Congress on Image and Signal Processing ◽

10.1109/cisp.2008.656 ◽

2008 ◽

Author(s):

Peijun Du ◽

Kun Tan ◽

Wei Zhang ◽

Zhigang Yan

Keyword(s):

Remotely Sensed ◽

Remotely Sensed Imagery ◽

Ann Classification

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Weakly Supervised Classification of Remotely Sensed Imagery Using Label Constraint and Edge Penalty

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2016.2623942 ◽

2017 ◽

Vol 55 (3) ◽

pp. 1424-1436 ◽

Author(s):

Linlin Xu ◽

David A. Clausi ◽

Fan Li ◽

Alexander Wong

Keyword(s):

Supervised Classification ◽

Remotely Sensed ◽

Remotely Sensed Imagery ◽

Weakly Supervised ◽

Weakly Supervised Classification

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Adaptive Parametric Estimation And Classification Of Remotely Sensed Imagery Using A Pyramid Structure

10.1109/igarss.1990.688823 ◽

2005 ◽

Author(s):

K. Kim ◽

M.M. Crawford

Keyword(s):

Remotely Sensed ◽

Parametric Estimation ◽

Remotely Sensed Imagery ◽

Pyramid Structure

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Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis

Remote Sensing of Environment ◽

10.1016/j.rse.2004.01.007 ◽

2004 ◽

Vol 90 (3) ◽

pp. 331-336 ◽

Author(s):

R Lawrence

Keyword(s):

Classification Tree ◽

Remotely Sensed ◽

Stochastic Gradient ◽

Gradient Boosting ◽

Classification Tree Analysis ◽

Tree Analysis ◽

Remotely Sensed Imagery ◽

Stochastic Gradient Boosting

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Support vector random field based approach towards object based classification of remotely sensed imagery

2013 IEEE International Conference on Signal Processing, Computing and Control (ISPCC) ◽

10.1109/ispcc.2013.6663455 ◽

2013 ◽

Author(s):

P V Arun

Keyword(s):

Random Field ◽

Remotely Sensed ◽

Support Vector ◽

Remotely Sensed Imagery ◽

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