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Hyperspectral Regression: Code Examples

This repository consists of additional material and exemplary implementations for our book chapter.

The code in this repository is provided via notebooks. The notebooks are structured as follows:

1. Data <notebooks/1_Data.ipynb>_
2. Features <notebooks/2_Features.ipynb>_
3. Supervised Learning <notebooks/3_Supervised_Learning.ipynb>_
4. Active Learning <notebooks/4_Active_Learning.ipynb>_
5. Model Selection and Evaluation <notebooks/5_Model_Selection_and_Evaluation.ipynb>_
6. Generative Adversarial Networks <notebooks/6_GANs.ipynb>_

Description

:License: 3-Clause BSD license <LICENSE>_

:Authors: Felix M. Riese <mailto:[email protected]>, Sina Keller <mailto:[email protected]>

:Citation: see Citation_

:Paper: Riese and Keller (2020) <https://doi.org/10.1007/978-3-030-38617-7_7>_

:Requirements: Python 3 with these packages <requirements.txt>_

How to use this repository?

1. Install Python 3, e.g. with Anaconda <https://www.anaconda.com/distribution/>_

2. Install the required packages

   conda install --file requirements.txt

3. Start jupyter

   jupyter notebook

4. Open the notebook folder in this repository in the Jupyter browser and select the desired notebook.

Citation

The bibtex file including both references is available in bibliography.bib <bibliography.bib>_.

Paper:

Felix M. Riese and Sina Keller, "Supervised, Semi-Supervised, and Unsupervised Learning for Hyperspectral Regression", in Hyperspectral Image Analysis: Advances in Machine Learning and Signal Processing, Saurabh Prasad and Jocelyn Chanussot, Eds. Cham: Springer International Publishing, 2020, ch. 7, pp. 187–232, doi:10.1007/978-3-030-38617-7_7 <https://doi.org/10.1007/978-3-030-38617-7_7>_.

.. code:: bibtex

@incollection{riese2020supervised,
    author = {Riese, Felix~M. and Keller, Sina},
    title ={{Supervised, Semi-Supervised, and Unsupervised Learning for
            Hyperspectral Regression}},
    booktitle = {{Hyperspectral Image Analysis: Advances in Machine
                 Learning and Signal Processing}},
    editor = {Prasad, Saurabh and Chanussot, Jocelyn},
    year = {2020},
    publisher = {Springer International Publishing},
    address = {Cham},
    chapter = {7},
    pages = {187--232},
    doi = {10.1007/978-3-030-38617-7_7},
}

Code:

Felix M. Riese and Sina Keller, "Hyperspectral Regression: Code Examples", Zenodo, doi:10.5281/zenodo.3450676 <http://doi.org/10.5281/zenodo.3450676>_, 2019.

.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3450676.svg :target: https://doi.org/10.5281/zenodo.3450676 :alt: DOI

.. code:: bibtex

@misc{riese2019hyperspectral,
    author = {Riese, Felix~M. and Keller, Sina},
    title = {{Hyperspectral Regression: Code Examples}},
    year = {2019},
    DOI = {10.5281/zenodo.3450676},
    publisher = {Zenodo},
    howpublished = {\href{https://doi.org/10.5281/zenodo.3450676}{doi.org/10.5281/zenodo.3450676}}
}