Optimal band selection for high dimensional remote sensing data using genetic algorithm

Mapping Intimacies ◽

10.1117/12.847907 ◽

2009 ◽

Cited By ~ 5

Author(s):

Xianfeng Zhang ◽

Quan Sun ◽

Jonathan Li

Keyword(s):

Remote Sensing ◽

Genetic Algorithm ◽

Remote Sensing Data ◽

High Dimensional ◽

Band Selection ◽

Sensing Data ◽

Selection For

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Band selection for high-dimensional remote sensing data by mutual information

2016 International Conference on Electrical and Information Technologies (ICEIT) ◽

10.1109/eitech.2016.7519625 ◽

2016 ◽

Author(s):

Ibtissam Banit'ouagua ◽

Mounir Ait Kerroum ◽

Ahmed Hammouch ◽

Driss Aboutajdine

Keyword(s):

Remote Sensing ◽

Mutual Information ◽

Remote Sensing Data ◽

High Dimensional ◽

Band Selection ◽

Sensing Data ◽

Selection For

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Feature selection for high-dimensional remote sensing data by maximum entropy principle based optimization

IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217) ◽

10.1109/igarss.2001.978336 ◽

2002 ◽

Author(s):

Shixin Yu ◽

P. Scheunders

Keyword(s):

Remote Sensing ◽

Feature Selection ◽

Maximum Entropy ◽

Maximum Entropy Principle ◽

Remote Sensing Data ◽

High Dimensional ◽

Sensing Data ◽

Entropy Principle ◽

Selection For

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Fuzzy Markov chains approach to feature selection for high dimensional remote sensing data

IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217) ◽

10.1109/igarss.2001.978337 ◽

2002 ◽

Cited By ~ 1

Author(s):

S. Yu ◽

P. Scheunders

Keyword(s):

Remote Sensing ◽

Feature Selection ◽

Markov Chains ◽

Remote Sensing Data ◽

High Dimensional ◽

Sensing Data ◽

Selection For

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Band selection for hyperspectral remote sensing data through correlation matrix to improve image clustering

10.1117/12.2027032 ◽

2013 ◽

Author(s):

Hamed Gholizadeh

Keyword(s):

Remote Sensing ◽

Correlation Matrix ◽

Remote Sensing Data ◽

Hyperspectral Remote Sensing ◽

Image Clustering ◽

Band Selection ◽

Sensing Data ◽

Selection For

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Recognition of High Dimensional Multi-Sensor Remote Sensing Data of Various Spatial Resolution

2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP) ◽

10.1109/dsmp47368.2020.9204186 ◽

2020 ◽

Author(s):

Volodymyr Hnatushenko ◽

Viktoriia Hnatushenko

Keyword(s):

Remote Sensing ◽

Spatial Resolution ◽

Remote Sensing Data ◽

High Dimensional ◽

Sensing Data

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FODSPO based feature selection for hyperspectral remote sensing data

2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) ◽

10.1109/whispers.2014.8077613 ◽

2014 ◽

Author(s):

Pedram Ghamisi ◽

Micael S. Couceiro ◽

Jon Atli Benediktsson

Keyword(s):

Remote Sensing ◽

Feature Selection ◽

Remote Sensing Data ◽

Hyperspectral Remote Sensing ◽

Sensing Data ◽

Selection For

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Feature selection for remote-sensing data classification

10.1117/12.196757 ◽

1994 ◽

Author(s):

Sebastiano B. Serpico ◽

Paolo Pellegretti ◽

Lorenzo Bruzzone

Keyword(s):

Remote Sensing ◽

Feature Selection ◽

Remote Sensing Data ◽

Data Classification ◽

Sensing Data ◽

Selection For

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Biomass retrieval from high-dimensional active/passive remote sensing data by using artificial neural networks

International Journal of Remote Sensing ◽

10.1080/014311697218863 ◽

1997 ◽

Vol 18 (4) ◽

pp. 971-979 ◽

Cited By ~ 42

Author(s):

Y.-Q. Jin ◽

C. Liu

Keyword(s):

Remote Sensing ◽

Neural Networks ◽

Artificial Neural Networks ◽

Remote Sensing Data ◽

High Dimensional ◽

Sensing Data ◽

Passive Remote Sensing ◽

Artificial Neural

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Genetic algorithm based new sequence of principal component regression (GA-NSPCR) for feature selection and yield prediction using hyperspectral remote sensing data

2012 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2012.6351743 ◽

2012 ◽

Cited By ~ 3

Author(s):

Sidik Mulyono ◽

Mohamad Ivan Fanany ◽

T Basaruddin

Keyword(s):

Remote Sensing ◽

Genetic Algorithm ◽

Feature Selection ◽

Principal Component Regression ◽

Remote Sensing Data ◽

Principal Component ◽

Hyperspectral Remote Sensing ◽

Yield Prediction ◽

Sensing Data

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Best Band Selection using Principle Component Analysis Algorithm from Remote Sensing Data

AL-Rafidain Journal of Computer Sciences and Mathematics ◽

10.33899/csmj.2010.163933 ◽

2010 ◽

Vol 7 (3) ◽

pp. 135-144

Author(s):

Maha Hasso ◽

Mona Siddiq

Keyword(s):

Remote Sensing ◽

Principle Component Analysis ◽

Remote Sensing Data ◽

Component Analysis ◽

Band Selection ◽

Analysis Algorithm ◽

Sensing Data ◽

Principle Component

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