Precision Recognition of Rock Thin Section Images With Multi‐Head Self‐Attention Convolutional Neural Networks
Abstract Lithological thin‐section image classification is crucial in geology. Traditional manual methods rely on expert experience, being subjective and time‐consuming. Convolutional neural network (CNN)‐based automated classification has potential but is less effective with more rock types and lim...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-06-01
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| Series: | Journal of Geophysical Research: Machine Learning and Computation |
| Online Access: | https://doi.org/10.1029/2025JH000617 |
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