Machine learning-based method enhances accuracy of measuring dip angles and directions in rock facets

Machine learning (ML) algorithms are constantly finding new applications in all scientific fields, and geological engineering is no exception. Over the last decade, researchers have developed various ML-based techniques to determine geological features more effortlessly in rocks, such as the dip angle (the angle at which a planar feature is inclined to the horizontal plane) and direction of rock facets in tunnels. Understanding these characteristics is essential for large construction projects as they help ensure structural stability and safety, preventing potential failures or collapses.