Interpretable Dual-Channel Convolutional Neural Networks for Lithology Identification Based on Multisource Remote Sensing Data
Lithology identification provides a crucial foundation for various geological tasks, such as mineral exploration and geological mapping. Traditionally, lithology identification requires geologists to interpret geological data collected from the field. However, the acquisition of geological data requ...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/7/1314 |
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