[HTML][HTML] The minerals industry in the era of digital transition: An energy-efficient and environmentally conscious approach

GT Nwaila, HE Frimmel, SE Zhang, JE Bourdeau… - Resources Policy, 2022 - Elsevier
The concept of the 4th industrial revolution is becoming a strategic determinant of
sustainability, success and competitiveness in the modern mining sector. The importance of …

Deep learning in image segmentation for mineral production: A review

Y Liu, X Wang, Z Zhang, F Deng - Computers & Geosciences, 2023 - Elsevier
Mineral image segmentation is widely used in mining, sorting, exploration, composition
analysis, and other production works. The burgeoning field of deep learning provides …

Smart contract privacy protection using AI in cyber-physical systems: tools, techniques and challenges

R Gupta, S Tanwar, F Al-Turjman, P Italiya… - IEEE …, 2020 - ieeexplore.ieee.org
Applications of Blockchain (BC) technology and Cyber-Physical Systems (CPS) are
increasing exponentially. However, framing resilient and correct smart contracts (SCs) for …

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 **
EE Baraboshkin, LS Ismailova, DM Orlov… - Computers & …, 2020 - Elsevier
The description of rocks is one of the most time-consuming tasks in the everyday work of a
geologist, especially when very accurate description is required. We here present a method …

Point-of-care pathogen testing using photonic crystals and machine vision for diagnosis of urinary tract infections

H Liu, Z Li, R Shen, Z Li, Y Yang, Q Yuan - Nano letters, 2021 - ACS Publications
Urinary tract infections (UTIs) caused by bacterial invasion can lead to life-threatening
complications, posing a significant health threat to more than 150 million people worldwide …

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 …

Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA

S Chatterjee, M Mastalerz, A Drobniak… - International Journal of …, 2022 - Elsevier
Rare earth elements and yttrium (REYs) are critical elements and valuable commodities due
to their limited availability and high demand in a wide range of applications and especially in …

Deep learning-based image classification for online multi-coal and multi-class sorting

Y Liu, Z Zhang, X Liu, L Wang, X **a - 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 …

Automatic segmentation of TBM muck images via a deep-learning approach to estimate the size and shape of rock chips

X Zhou, Q Gong, Y Liu, L Yin - Automation in Construction, 2021 - Elsevier
Real-time muck analysis is of great importance for assisting tunnel boring machines (TBMs)
in intelligent tunneling. Typically, muck images are characterized by low contrast, large …