Machine learning applications in minerals processing: A review
JT McCoy, L Auret - Minerals Engineering, 2019 - Elsevier
Abstract Machine learning and artificial intelligence techniques have an ever-increasing
presence and impact on a wide-variety of research and commercial fields. Disappointed by …
presence and impact on a wide-variety of research and commercial fields. Disappointed by …
Recent advances in flotation froth image analysis
Abstract Machine vision is widely used in the monitoring of froth flotation plants as a means
to assist control operators on the plant. While these systems have a mature ability to analyse …
to assist control operators on the plant. While these systems have a mature ability to analyse …
Ore image classification based on small deep learning model: Evaluation and optimization of model depth, model structure and data size
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 …
Flotation froth image recognition with convolutional neural networks
Computer vision systems designed for flotation froth image analysis are well established in
industry, where their ability to measure froth flow velocities and stability are used to control …
industry, where their ability to measure froth flow velocities and stability are used to control …
Flotation froth image classification using convolutional neural networks
In recent years, the use of machine vision systems for monitoring and control of the flotation
plants has significantly increased. The classification of froth images is a critical step in …
plants has significantly increased. The classification of froth images is a critical step in …
An intelligent modelling framework for mechanical properties of cemented paste backfill
The mechanical properties of cemented paste backfill (CPB) are particularly important for its
application in the minerals industry. In practice, a large number of cumbersome and time …
application in the minerals industry. In practice, a large number of cumbersome and time …
Deep learning-based ash content prediction of coal flotation concentrate using convolutional neural network
Z Wen, C Zhou, J Pan, T Nie, C Zhou, Z Lu - Minerals Engineering, 2021 - Elsevier
Convolutional neural networks, as the current state-of-the-art in image classification, are
regarded as a promising way for flotation soft sensors based on froth images. This paper …
regarded as a promising way for flotation soft sensors based on froth images. This paper …
Ash determination of coal flotation concentrate by analyzing froth image using a novel hybrid model based on deep learning algorithms and attention mechanism
Flotation is an important separation method for coal preparation, where ash content is critical
to coal product quality. However, the absence of fast and accurate ash determination of coal …
to coal product quality. However, the absence of fast and accurate ash determination of coal …
Deep learning-based image classification for online multi-coal and multi-class sorting
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 …
A sequential cross-product knowledge accumulation, extraction and transfer framework for machine learning-based production process modelling
Machine learning is a promising method to model production processes and predict product
quality. It is challenging to accurately model complex systems due to data scarcity, as mass …
quality. It is challenging to accurately model complex systems due to data scarcity, as mass …