The automated interpretation of rock structure can improve the efficiency, accuracy, and
consistency of the geological risk assessment of tunnel face. Because of the high …

Rock classification plays an important role in rock mechanics, petrology, mining
engineering, magmatic processes, and numerous other fields pertaining to geosciences …

An intelligent lithology identification method is proposed based on deep learning of the rock
microscopic images. Based on the characteristics of rock images in the dataset, we used …

One early sign of tunnel structure deterioration originates in the form of cracking, and
therefore crack detection and resultant classification is integral for tunnel structural …

This paper proposes an image-based method for automated rock fracture segmentation and
fracture trace quantification. It is integrated using a CNN-based model named FraSegNet, a …

Accurately acquiring the geological information of the tunnel face will help to set the optimal
operational parameters, so that the shield machine can achieve better tunneling …

An intelligent lithology identification method is proposed based on the deep learning of rock
images. The lithology information and position information in rock images can be predicted …

In Mars exploration, rocks are good targets for compositional analysis with spectrometers.
Their shape, size, and texture could provide a wealth of information for study of planetary …

The performance of traditional visual inspection by handcrafted features for crack and
leakage defects of metro shield tunnel is hardly satisfactory nowadays because it is low …

The overall assessment of tunnel lining, including shapes, categories, and depths of tunnel
internal defects as well as the thickness of tunnel linings is vital to the safe operation of …