Mineral characterization using scanning electron microscopy (SEM): a review of the fundamentals, advancements, and research directions
Featured Application The focus of this review is the use of SEM imaging to gain insight into
the composition and morphology of minerals in view of predicting or understanding their …
the composition and morphology of minerals in view of predicting or understanding their …
Ore image classification based on small deep learning model: Evaluation and optimization of model depth, model structure and data size
Y Liu, Z Zhang, X Liu, L Wang, X Xia - Minerals Engineering, 2021 - Elsevier
The ore image classification technology based on deep learning is an effective way to
improve the image sensor-based ore sorting classification capability. However, in practice …
improve the image sensor-based ore sorting classification capability. However, in practice …
[HTML][HTML] Mineral prospectivity mapping integrated with geological map knowledge graph and geochemical data: A case study of gold deposits at Raofeng area …
Q Yan, L Xue, Y Li, R Wang, B Wu, K Ding, J Wang - Ore Geology Reviews, 2023 - Elsevier
The knowledge graph in geological applications is highly regarded, and its usefulness
requires the support of geological survey data. Therefore, this paper proposes a mineral …
requires the support of geological survey data. Therefore, this paper proposes a mineral …
[PDF][PDF] 基于机器学习的矿物智能识别方法研究进展与展望
郝慧珍， 顾庆， 胡修棉 - 地球科学, 2021 - researchgate.net
矿物智能识别是地球科学与信息科学的重要交叉方向, 显示出强大的生命力.
本文在调研国内外研究动态的基础上, 把矿物智能识别划分为4 个阶段, 即矿物采集, 数据获取 …
本文在调研国内外研究动态的基础上, 把矿物智能识别划分为4 个阶段, 即矿物采集, 数据获取 …
[HTML][HTML] Deep learning of rock microscopic images for intelligent lithology identification: Neural network comparison and selection
Z Xu, W Ma, P Lin, Y Hua - Journal of Rock Mechanics and Geotechnical …, 2022 - Elsevier
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 …
microscopic images. Based on the characteristics of rock images in the dataset, we used …
When petrophysics meets big data: What can machine do?
Petrophysics is a pivotal discipline that bridges engineering and geosciences for reservoir
characterization and development. New sensor technologies have enabled real-time …
characterization and development. New sensor technologies have enabled real-time …
MineralImage5k: A benchmark for zero-shot raw mineral visual recognition and description
S Nesteruk, J Agafonova, I Pavlov, M Gerasimov… - Computers & …, 2023 - Elsevier
Mineral image recognition is a challenging computer vision problem. Without external tools,
even a human expert cannot distinguish some mineral species accurately. Previous …
even a human expert cannot distinguish some mineral species accurately. Previous …
Fully automated carbonate petrography using deep convolutional neural networks
Carbonate rocks are important archives of past ocean conditions as well as hosts of
economic resources such as hydrocarbons, water, and minerals. Geologists typically …
economic resources such as hydrocarbons, water, and minerals. Geologists typically …
Deep learning-based image classification for online multi-coal and multi-class sorting
Y Liu, Z Zhang, X Liu, L Wang, X Xia - Computers & Geosciences, 2021 - Elsevier
Deep learning is an effective way to improve the classification accuracy of coal images for
the machine vision-based coal sorting. However, the related research on deep learning …
the machine vision-based coal sorting. However, the related research on deep learning …
Rock images classification by using deep convolution neural network
G Cheng, W Guo - Journal of Physics: Conference Series, 2017 - iopscience.iop.org
Granularity analysis is one of the most essential issues in authenticate under microscope. To
improve the efficiency and accuracy of traditional manual work, an convolutional neural …
improve the efficiency and accuracy of traditional manual work, an convolutional neural …