Recognition of mineralization-related anomaly patterns through an autoencoder neural network for mineral exploration targeting
In mineral potential mapping, supervised machine learning algorithms have shown great promise in delineating and prioritizing potential areas. However, since mineralization being a relatively rare geological event, most supervised machine learning-based models face substantial challenges in properly...
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Published in | Applied geochemistry Vol. 158; p. 105807 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
01.11.2023
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Subjects | |
Online Access | Get full text |
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