tutorial-ugm-hyperspectral

A Tutorial on Modeling and Inference in Undirected Graphical Models for Hyperspectral Image Analysis

https://github.com/ubgewali/tutorial-ugm-hyperspectral

Science Score: 51.0%

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    Found 1 DOI reference(s) in README
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    Links to: arxiv.org
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Keywords

conditional-random-fields graphical-models hyperspectral hyperspectral-image-classification markov-random-field
Last synced: 6 months ago · JSON representation ·

Repository

A Tutorial on Modeling and Inference in Undirected Graphical Models for Hyperspectral Image Analysis

Basic Info
  • Host: GitHub
  • Owner: UBGewali
  • Language: Matlab
  • Default Branch: master
  • Homepage:
  • Size: 33.2 KB
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Topics
conditional-random-fields graphical-models hyperspectral hyperspectral-image-classification markov-random-field
Created about 8 years ago · Last pushed almost 8 years ago
Metadata Files
Readme Citation

README.md

A Tutorial on Modeling and Inference in Undirected Graphical Models for Hyperspectral Image Analysis

This repository contains MATLAB code to reproduce the results in

U. B. Gewali and S. T. Monteiro. "A tutorial on modelling and inference in undirected graphical models for hyperspectral image analysis." International Journal of Remote Sensing (2018): 1-40. [article][bibtex][preprint]

Usage

Download and install datasets and toolboxes

```matlab

make ```

Run Experiments

Experiment 1: (Tables 1-5 in the paper)

matlab run_expt1

Experiment 2: (Tables 6-9 in the paper)

matlab run_expt2

Owner

  • Login: UBGewali
  • Kind: user

Citation (citation.bib)

@article{gewali2018tutorial,
  title={A tutorial on modelling and inference in undirected graphical models for hyperspectral image analysis},
  author={Gewali, Utsav B and Monteiro, Sildomar T},
  journal={International Journal of Remote Sensing},
  pages={1--40},
  year={2018},
  publisher={Taylor \& Francis}
}

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