Identifying mineral potentials related to geological structures using deep learning

Authors

  • hadi shahraki University of Sistan and Baluchesta
  • Mohsen Jami

DOI:

https://doi.org/10.6977/IJoSI.202602_10(1).0002

Abstract

Artificial intelligence is increasingly being used as a powerful tool in various industries, including earth sciences. Geological structures play an undeniable role in the formation of mineral potentials. Investigating these structures relies on image and satellite data observations, as well as expert opinions, which can be a time-consuming process. Artificial intelligence can serve as a useful tool to expedite this process and enhance the accuracy of mineral potential identification. This article presents a new model based on deep neural networks for identifying mineral potentials. The unique feature of the proposed method is the incorporation of morphological data alongside multi-spectral data to identify mineral potentials. To evaluate the effectiveness of the proposed method, ASTER satellite images from a region in the southeast of Iran were utilized. The obtained results demonstrate an improvement in the accuracy of the proposed method compared to similar approaches.

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Published

2026-02-26

Issue

Vol. 10 No. 1 (2026): International Journal of Systematic Innovation

Section

Regular full papers

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