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

Rock classification from petrographic thin section analysis often requires expertise in
mineralogy. This study developed a deep learning approach based on a convolutional …

The automatic identification of rock type in the field would aid geological surveying,
education, and automatic mapping. Deep learning is receiving significant research attention …

Rock classification provides vital information to geosciences and geological engineering
practices. Reaping the benefits of the advances of computer vision-based deep learning …

Rock image classification is a significant part of geological research. Compared with
traditional image classification methods, rock image classification methods based on deep …

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 …

In order to enhance the ability to represent rock feature information and finally improve the
rock identification performance of convolution neural networks (CNN), a new pooling mode …

Convolutional neural networks (CNN) are currently the most widely used tool for the
classification of images, especially if such images have large within-and small between …

The optical features of mineral composition and texture in petrographic thin sections are an
important basis for rock identification and rock evolution analysis. However, the efficiency …

The recognition and classification of rock lithology is an extremely important task of
geological surveys. This paper proposes a new method for quickly identifying multiple types …