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What is Machine Learning for Lithological Mapping about?

This study evaluates machine learning algorithms for lithological mapping using ASTER remote-sensing data in the Sar-Cheshmeh copper mining region of Iran. Various algorithms, including random forest, support vector machine, gradient boosting, extreme gradient boosting, and deep learning, were assessed for their accuracy in identifying lithological features, achieving overall accuracies ranging from 80% to 85%. The findings highlight the effectiveness of machine learning techniques in enhancing geological s

Author

jaqv76

Language

EN