Convolutional neural networks provide a state-of-the-art approach to the development of
froth image sensors. In this study, it is shown that a pretrained neural network architecture …

The use of computer vision systems to monitor flotation froths hass become widely
established over the last few decades. Features extracted from images of the froth can be …

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 …

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 …

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 …

Accurate and timely investigation to concentrate grade in mining industry is a premise of
realizing real time and efficient control in a froth flotation process. This study seeks to use …

Image-based soft sensors are of interest in process industries due to their cost-effective and
non-intrusive properties. Unlike most multivariate inputs, images are highly dimensional …

The froth feature extraction plays an important role in flotation circuit monitoring. Given the
low efficiency of hand-crafted features and the poor interpretability of high-dimensional …

Deep learning constitutes a significant recent advance in machine learning and has been
particularly successful in applications related to image processing, where it can already …

Froth flotation is widely used in mineral processing to separate valuable mineral ores from
gangue or waste material. As such, improved monitoring and control of flotation systems can …