Rapid rock mass classification framework using machine learning and semantic segmentation for underground mining

doi:10.1016/j.engappai.2025.111530

Rapid rock mass classification framework using machine learning and semantic segmentation for underground mining

2025-07-18

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DOI：10.1016/j.engappai.2025.111530

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• GNN outperforms tree models in predicting rock UCS from field tests. • U-Net outperforms FCN-8s and SegNet in rock joint fracture segmentation. • Proposed a multi-stage clustering-fitted algorithm to extracts joint parameters. • AI-based classification method performs better in ore body than surrounding rock. • RMR classification system is more suitable for the image-based AI framework.

Rapid rock mass classification framework using machine learning and semantic segmentation for underground mining

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