Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 7
Articles | Volume 19, issue 7
https://doi.org/10.5194/gmd-19-2593-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-2593-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 7
Model description paper
 | 
07 Apr 2026
Model description paper |  | 07 Apr 2026

DEEP-SEAM: an explainable semi-supervised deep learning framework for mineral prospectivity mapping

Zijing Luo, Ehsan Farahbakhsh, Stephen Hore, and R. Dietmar Müller

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Short summary
By combining multi-source data with advanced processing techniques, our deep learning model effectively identifies mineralisation patterns despite extremely limited deposit samples, analyses data and validates the geological relevance of its decisions through explainability analysis, providing a universally reliable solution for artificial intelligence-assisted mineral prospectivity mapping.
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