Explainable deep learning for automatic rock classification

Published: 01 Jan 2024, Last Modified: 13 Nov 2024Comput. Geosci. 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•Proposed dual network achieves high accuracy (0.99) and interpretable feature extractions for sedimentary rock classification.•Regular DL models achieved high accuracy (>0.94), but relied on irrelevant features for classification.•This study emphasizes importance of interpretability and geological knowledge in developing DL models for geosciences.
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