spectralcov-gp-mtgp

Gaussian Processes for Vegetation Parameter Estimation from Hyperspectral Data with Limited Ground Truth

https://github.com/ubgewali/spectralcov-gp-mtgp

Science Score: 41.0%

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  • CITATION.cff file
    Found CITATION.cff file
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    Found 2 DOI reference(s) in README
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Keywords

gaussian-processes hyperspectral vegetation-analysis

Keywords from Contributors

multispectral super-resolution
Last synced: 11 months ago · JSON representation ·

Repository

Gaussian Processes for Vegetation Parameter Estimation from Hyperspectral Data with Limited Ground Truth

Basic Info
  • Host: GitHub
  • Owner: UBGewali
  • Language: MATLAB
  • Default Branch: master
  • Size: 15.6 KB
Statistics
  • Stars: 5
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
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Topics
gaussian-processes hyperspectral vegetation-analysis
Created over 6 years ago · Last pushed over 6 years ago
Metadata Files
Readme Citation

README.md

Gaussian Processes for Vegetation Parameter Estimation from Hyperspectral Data with Limited Ground Truth

This repository contains MATLAB code for vegetation paramter estimation from hyperspectral data using single/multi-task Gaussian process with covariance functions based on well-established spectral comparison metrics.

Run demo code

GP with spectral covariance functions

```matlab

test_GP ```

Multitask GP with spectral covariance functions

matlab test_MTGP

Citation

Please consider citing the following article if you use the code in this repository:

U. B. Gewali, S. T. Monteiro and E. Saber, "Gaussian processes for vegetation parameter estimation with limited ground truth," Remote Sensing, 2019. [article][bibtex]

Contact

Utsav Gewali (ubg9540@rit.edu)

Owner

  • Login: UBGewali
  • Kind: user

Citation (citation.bib)

@article{gewali2019gaussian,
  title={Gaussian Processes for Vegetation Parameter Estimation from Hyperspectral Data with Limited Ground Truth},
  author={Gewali, Utsav B and Monteiro, Sildomar T and Saber, Eli},
  journal={Remote Sensing},
  volume={11},
  number={13},
  pages={1614},
  year={2019},
  publisher={Multidisciplinary Digital Publishing Institute}
}

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