EXPLORATION OF IOCG MINERALIZATIONS USING INTEGRATION OF SPACE-BORNE REMOTE SENSING DATA WITH AIRBORNE GEOPHYSICAL DATA

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3. A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data H. Shirmard et al. 10.3390/rs14040819
4. Extracting geological and alteration information and predicting antimony ore based on multisource remote sensing data in Huangyangling, Xinjiang D. Wang et al. 10.3389/feart.2024.1366727
5. Improving Geological Remote Sensing Interpretation via Optimal Transport-Based Point–Surface Data Fusion J. Wu et al. 10.3390/rs16010053
6. Review on the development of multi- and hyperspectral remote sensing technology for exploration of copper–gold deposits F. Yao et al. 10.1016/j.oregeorev.2023.105732
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8. PRISMA hyperspectral data for lithological mapping in the Egyptian Eastern Desert: Evaluating the support vector machine, random forest, and XG boost machine learning algorithms A. Shebl et al. 10.1016/j.oregeorev.2023.105652
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