28-space.Rmd

# MI²Space {.unnumbered #mi2space}

<img src="images/intro-space.png" style="width: 95%;">

**MI²Space Team** develops methods, software, and systems for the validation, debugging and auditing of artificial intelligence algorithms used in space missions. The research is being conducted for the [European Space Agency](https://www.esa.int/").


#### Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI {-}

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<img src="images/redteaming_hsi.png" align="left">
<a href="https://doi.org/10.48550/arXiv.2403.08017">Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI</a>
<p> Vladimir Zaigrajew, Hubert Baniecki, Lukasz Tulczyjew, Agata M. Wijata, Jakub Nalepa, Nicolas Longépé, Przemyslaw Biecek</p>
<p><strong>ICLR Workshops (2024)</strong></p>
Remote sensing applications require machine learning models that are reliable and robust, highlighting the importance of red teaming for uncovering flaws and biases. We introduce a novel red teaming approach for hyperspectral image analysis, specifically for soil parameter estimation in the Hyperview challenge. Utilizing SHAP for red teaming, we enhanced the top-performing model based on our findings. Additionally, we introduced a new visualization technique to improve model understanding in the hyperspectral domain.
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