4.7 Article

Recent advances in flotation froth image analysis

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Artificial Intelligence

ASM-VoFDehaze: a real-time defogging method of zinc froth image

Wenhui Xiao et al.

Summary: This research proposes a real-time defogging method based on ASM-VoFD for defogging flotation froth images in low temperature environment. The experiments show that the algorithm has a good defogging effect on industrial images and meets the application requirements of real-time flotation monitoring.

CONNECTION SCIENCE (2022)

Article Physics, Multidisciplinary

FS-DeblurGAN: a spatiotemporal deblurring method for zinc froth flotation

Wenhui Xiao et al.

Summary: Research on flotation froth image deblurring is important for zinc flotation working condition recognition and fault diagnosis. A new deblurring method called filter-spatiotemporal-DeblurGAN (FS-DeblurGAN) was proposed, which significantly improves the deblurring effect and adapts to froth images under different conditions.

EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS (2022)

Article Metallurgy & Metallurgical Engineering

Flotation Froth Phase Bubble Size Measurement

C. Bhondayi

Summary: This paper reviews methods for measuring bubble sizes in mineral froth flotation, including industrial machine vision and traditional photographic methods. It also introduces new methods for overcoming limitations of transparent systems and measuring bubble sizes within the froth/foam. However, further testing is needed for these methods.

MINERAL PROCESSING AND EXTRACTIVE METALLURGY REVIEW (2022)

Review Computer Science, Artificial Intelligence

High performance accelerators for deep neural networks: A review

Mohd Saqib Akhoon et al.

Summary: The availability of huge structured and unstructured data, advanced memory technologies, and high-performance computing machines have driven the development of artificial intelligence (AI) and machine learning (ML). However, challenges such as processing speed, memory requirements, and connectivity issues still need to be addressed. To overcome these challenges, state-of-the-art DNN accelerators have been designed and implemented, but there is room for further improvement and research in this area.

EXPERT SYSTEMS (2022)

Article Engineering, Chemical

An unsupervised method for extracting semantic features of flotation froth images

Xu Wang et al.

Summary: This paper proposes a method to convert flotation froth image data into a latent semantic space and automatically extract semantic features. Experimental results show that the extracted features can be visually interpreted and effectively used in flotation condition recognition and grade prediction. This is the first report demonstrating the use of generative adversarial networks to improve the interpretability of froth image features.

MINERALS ENGINEERING (2022)

Article Computer Science, Artificial Intelligence

A new froth image classification method based on the MRMR-SSGMM hybrid model for recognition of reagent dosage condition in the coal flotation process

Wenyan Cao et al.

Summary: This study proposes a new froth image classification method based on the MR MR-SSGMM hybrid model for recognizing reagent dosage condition in the coal flotation process. By extracting features and optimizing selection, it achieves high accuracy classification results for froth images.

APPLIED INTELLIGENCE (2022)

Article Automation & Control Systems

Disturbance-Encoding-Based Neural Hammerstein-Wiener Model for Industrial Process Predictive Control

Jin Zhang et al.

Summary: This study proposes a model predictive control technique based on the HW model, which improves the control reliability by introducing a disturbance encoder and an observer. The superiority and effectiveness of the proposed method have been demonstrated through simulation and industrial application.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2022)

Article Materials Science, Multidisciplinary

Deep Learning Approaches to Image Texture Analysis in Material Processing

Xiu Liu et al.

Summary: This study compares traditional texture analysis methods with transfer learning approaches based on deep learning in simulated and real-world case studies, finding that deep learning methods achieve better results after retraining.

METALS (2022)

Article Environmental Sciences

Interpretation of Convolutional Neural Networks for Acid Sulfate Soil Classification

Amelie Beucher et al.

Summary: CNNs, originally used for computer vision, are now being applied to digital soil mapping. Explainable AI methods help clarify complex models like CNNs.

FRONTIERS IN ENVIRONMENTAL SCIENCE (2022)

Article Engineering, Industrial

A digital twin dosing system for iron reverse flotation

Dingsen Zhang et al.

Summary: This research designed a digital twin system for iron reverse flotation reagents based on digital twin technology and machine learning algorithms. The system can monitor the product quality in real-time, automatically update the reagent system, avoid reagent waste, and improve production efficiency.

JOURNAL OF MANUFACTURING SYSTEMS (2022)

Article Computer Science, Artificial Intelligence

An ensemble learning method based on deep neural network and group decision making

Xiaojun Zhou et al.

Summary: This paper proposes an ensemble learning method based on deep neural network and group decision making. Multiple deep neural networks are used to generate individual learners, and group decision making is applied to find the optimal alternative. Experimental results demonstrate the effectiveness and superiority of this method in image classification.

KNOWLEDGE-BASED SYSTEMS (2022)

Article Engineering, Multidisciplinary

A novel hybrid model for flow image segmentation and bubble pattern extraction

Yuanyuan Ju et al.

Summary: In this paper, a novel hybrid image analysis model (U-net-QR-EMD) combining the U-net algorithm with the quantile regression method (QR) and empirical mode decomposition (EMD) is proposed for bubble recognition in low-quality images. The model proves to be effective in identifying irregularly shaped bubbles and can accurately measure various bubble parameters. Additionally, the use of quantile regression and empirical mode decomposition provides more stable and periodic results.

MEASUREMENT (2022)

Article Engineering, Multidisciplinary

A machine learning approach to determine bubble sizes in foam at a transparent wall

Leon Knuepfer et al.

Summary: This article discusses the use of machine learning to measure the sizes of polyhedral bubble foam in contact with a transparent wall. By training a neural network model, the images can be accurately segmented and the distribution of bubble sizes can be obtained.

MEASUREMENT SCIENCE AND TECHNOLOGY (2022)

Article Engineering, Chemical

FlotGAIL: An operational adjustment framework for flotation circuits using generative adversarial imitation learning

Xu Wang et al.

Summary: In many industrial flotation processes, operational adjustment is still manual and based on individual experience. To resolve this, the study proposes an automatic operational adjustment framework based on generative adversarial imitation learning, which learns from expert demonstrations to control concentrate grade and recovery.

MINERALS ENGINEERING (2022)

Article Engineering, Chemical

Application of density-based clustering algorithm and capsule network to performance monitoring of antimony flotation process

Lihui Cen et al.

Summary: This paper presents the application of a capsule network called Froth-CapsNet to predict the antimony grade of pulp in a roughing cell of an antimony flotation plant. An improved density-based clustering algorithm is used to eliminate abnormal images from the training dataset. The Froth-CapsNet model can guide operators to adjust the dosage of flotation reagents in real-time and improve the antimony recovery rate.

MINERALS ENGINEERING (2022)

Article Computer Science, Artificial Intelligence

Generative adversarial network-based image-level optimal setpoint calculation for flotation reagents control

Jin Zhang et al.

Summary: This study proposes a SetpointGAN model based on generative adversarial network for calculating optimal setpoints in computer vision-based flotation reagent control. By introducing feature consistency loss and feed consistency loss, the model can better maintain the visual and control consistency between synthesized setpoints and ground-truth setpoints. Experimental results demonstrate the effectiveness of SetpointGAN and its advantages over existing methods.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Article Energy & Fuels

Prediction of the Ash Content of Flotation Concentrate Based on Froth Image Processing and BP Neural Network Modeling

Mengcheng Tang et al.

Summary: A real-time prediction system based on image processing and BP neural network modeling was established to monitor the flotation process and predict concentrate ash content for timely adjustment of flotation conditions. The predicted values from the model agree well with the actual values, showing the effectiveness of the system.

INTERNATIONAL JOURNAL OF COAL PREPARATION AND UTILIZATION (2021)

Article Automation & Control Systems

Data-driven adaptive modeling method for industrial processes and its application in flotation reagent control

Jin Zhang et al.

Summary: Efforts are devoted to enabling data-driven process models with incremental learning ability. A novel incremental learning method is proposed for process model updating. Experimental results demonstrate that the newly developed adaptive process model can accommodate new process excitation patterns and preserve its performance on old patterns.

ISA TRANSACTIONS (2021)

Article Engineering, Chemical

Long short-term memory-based grade monitoring in froth flotation using a froth video sequence

Hu Zhang et al.

Summary: This study proposes a grade monitoring model for zinc flotation circuit using LSTM network to incorporate unlabelled froth video information, effectively solving the problem of different sample rates. Experimental results demonstrate the effectiveness of the proposed model, showing a decrease in root mean squared error and an increase in R-squared score compared to traditional neural network models without unlabelled froth videos.

MINERALS ENGINEERING (2021)

Article Computer Science, Information Systems

Deep learning feature-based setpoint generation and optimal control for flotation processes

Mingxi Ai et al.

Summary: By integrating deep learning features and optimal control scheme, we have successfully proposed a method that can improve the performance of flotation process control. The new method consists of two layers of control, with the first layer generating setpoints based on fuzzy association rule reasoning and the second layer learning from historical records through conservative double Q-learning control.

INFORMATION SCIENCES (2021)

Article Engineering, Chemical

Deep learning-based ash content prediction of coal flotation concentrate using convolutional neural network

Zhiping Wen et al.

Summary: This paper presents a flotation soft sensor solution that predicts the concentrate ash content of coal flotation using froth images and convolutional neural networks. Through analyzing the classification performance and abstract pixel features of various CNN models, it was found that the fine-tuned ResNet_101 network achieved the highest classification accuracy and good industrial performance.

MINERALS ENGINEERING (2021)

Article Engineering, Industrial

Soft sensor of flotation froth grade classification based on hybrid deep neural network

Dingsen Zhang et al.

Summary: This study utilizes deep learning technology and transfer learning method to design a soft sensor for the classification of iron ore tailings grade, achieving an accuracy of 97%. A software system is developed to operate stably in the flotation plant.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH (2021)

Article Automation & Control Systems

Illumination-Invariant Flotation Froth Color Measuring via Wasserstein Distance-Based CycleGAN With Structure-Preserving Constraint

Jinping Liu et al.

Summary: The study introduces an illumination-invariant method for measuring froth color, utilizing a Wasserstein distance-based structure-preserving CycleGAN. The proposed method successfully maintains color features of froth images under various lighting conditions while preserving structure and texture invariance. The approach shows potential for online monitoring of flotation concentrate grade in industrial applications.

IEEE TRANSACTIONS ON CYBERNETICS (2021)

Review Geochemistry & Geophysics

Laser-Induced Breakdown Spectroscopy - A geochemical tool for the 21st century

Russell S. Harmon et al.

Summary: Laser-induced breakdown spectroscopy (LIBS) is a versatile atomic emission spectroscopy technique that allows for elemental analysis in a variety of environments and has vast potential for applications in the geosciences.

APPLIED GEOCHEMISTRY (2021)

Article Computer Science, Artificial Intelligence

Froth image clustering with feature semi-supervision through selection and label information

Wenyan Cao et al.

Summary: The paper proposes a method of froth image clustering with feature semi-supervision to achieve accurate control of reagent dosage and quality identification in coal flotation process, reducing costs and improving economic benefits to advance intelligent flotation development.

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS (2021)

Article Computer Science, Information Systems

Visual Perception-Based Fault Diagnosis in Froth Flotation Using Statistical Approaches

Jin Zhang et al.

Summary: This paper introduces a computer vision-aided fault detection and diagnosis approach for froth flotation, which includes the design of texture features, rejection sampling technique, fault detection using isolation forest, and fault diagnosis model based on spline regression. Simulation experiments and tests conducted on a lead-zinc flotation plant in China have demonstrated the effectiveness of the proposed method.

TSINGHUA SCIENCE AND TECHNOLOGY (2021)

Article Automation & Control Systems

Learning Local Gabor Pattern-Based Discriminative Dictionary of Froth Images for Flotation Process Working Condition Monitoring

Jinping Liu et al.

Summary: This article introduces a discrimination method for online flotation process working condition based on the sparse representation of froth images, achieving accurate FPWC identification by learning discriminative dictionary and linear classification model. To ensure adaptability, an incremental learning-based online model updating procedure is proposed.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)

Article Engineering, Chemical

Froth image feature engineering-based prediction method for concentrate ash content of coal flotation

Zhiping Wen et al.

Summary: Machine vision and machine learning have been widely researched in froth flotation, with feature engineering and principal component analysis showing promising results in predicting coal flotation concentrate ash content. The study highlighted the importance of utilizing advanced techniques like support vector regression and correlation matrices for improved predictions and practical industry applications.

MINERALS ENGINEERING (2021)

Article Engineering, Chemical

A layered working condition perception integrating handcrafted with deep features for froth flotation

Xiaoliang Gao et al.

Summary: The method integrates handcrafted features and deep features to recognize the working condition in zinc flotation; a layered evaluation agency is established to determine if reidentification is needed, and deep features with support vector machine are applied for reidentification under specific working conditions.

MINERALS ENGINEERING (2021)

Article Geochemistry & Geophysics

Monitoring of Flotation Systems by Use of Multivariate Froth Image Analysis

Chris Aldrich et al.

Summary: This study demonstrates that froth image analysis can be integrated with traditional multivariate statistical process monitoring methods for reliable monitoring of industrial platinum metal group flotation plants.

MINERALS (2021)

Article Engineering, Electrical & Electronic

Fault Diagnosis for Electro-Mechanical Actuators Based on STL-HSTA-GRU and SM

Xiaoyu Zhang et al.

Summary: In this study, a novel algorithm combining HSTA-GRU and STL is proposed to predict multiple time-series data for enhanced fault diagnosis of EMAs. By extracting seasonal factors and capturing spatio-temporal relationships among multivariate EMA sensors, the algorithm improves time series prediction and fault classification efficiency.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)

Proceedings Paper Computer Science, Artificial Intelligence

GraphSVX: Shapley Value Explanations for Graph Neural Networks

Alexandre Duval et al.

Summary: The paper proposes a unified framework for most GNN explainers and introduces GraphSVX, a specially designed explanation method for GNNs. GraphSVX captures the contribution of each feature and node to the prediction by constructing a surrogate model, ultimately providing Shapley Values as explanations.

MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2021: RESEARCH TRACK, PT II (2021)

Article Engineering, Electrical & Electronic

Two-Stream Deep Feature-Based Froth Flotation Monitoring Using Visual Attention Clues

Mingxi Ai et al.

Summary: This study developed a deep learning-based two-stream feature extraction model to extract froth appearance and movement features, and proposed a hybrid prediction model that includes a time-series analysis module and an attention mechanism to establish the prediction relationship between image features and concentrate grade. Comparison experiments using historical industry data confirmed the superiority of the proposed monitoring method, with industrial experiments achieving a coefficient of determination of 0.9256, representing a 7.9% improvement over an existing expert system.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)

Article Computer Science, Artificial Intelligence

Fuzzy association rule-based set-point adaptive optimization and control for the flotation process

Mingxi Ai et al.

NEURAL COMPUTING & APPLICATIONS (2020)

Article Automation & Control Systems

Timed key-value memory network for flotation reagent control

Jin Zhang et al.

CONTROL ENGINEERING PRACTICE (2020)

Article Engineering, Chemical

On the correlation between froth stability and viscosity in flotation

Chao Li et al.

MINERALS ENGINEERING (2020)

Article Computer Science, Information Systems

Deep Reinforcement Learning for Image Hashing

Yuxin Peng et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2020)

Article Engineering, Chemical

Convolutional memory network-based flotation performance monitoring

Jin Zhang et al.

MINERALS ENGINEERING (2020)

Article Engineering, Chemical

Flotation froth image classification using convolutional neural networks

M. Zarie et al.

MINERALS ENGINEERING (2020)

Article Engineering, Electrical & Electronic

Online Monitoring of Flotation Froth Bubble-Size Distributions via Multiscale Deblurring and Multistage Jumping Feature-Fused Full Convolutional Networks

Jinping Liu et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)

Proceedings Paper Automation & Control Systems

Flotation bubble size distribution detection based on semantic segmentation

Lei Zhang et al.

IFAC PAPERSONLINE (2020)

Proceedings Paper Automation & Control Systems

A survey on the status of industrial flotation control

J. D. le Roux et al.

IFAC PAPERSONLINE (2020)

Article Computer Science, Artificial Intelligence

Deep learning architectures in emerging cloud computing architectures: Recent development, challenges and next research trend

Fatsuma Jauro et al.

APPLIED SOFT COMPUTING (2020)

Article Automation & Control Systems

Dual-Rate Operational Optimal Control for Flotation Industrial Process With Unknown Operational Model

Yi Jiang et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2019)

Article Geography, Physical

3D gray level co-occurrence matrix and its application to identifying collapsed buildings

Luis Moya et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2019)

Article Engineering, Chemical

Flotation froth image recognition with convolutional neural networks

Y. Fu et al.

MINERALS ENGINEERING (2019)

Article Engineering, Chemical

Machine vision based monitoring and analysis of a coal column flotation circuit

M. Massinaei et al.

POWDER TECHNOLOGY (2019)

Article Engineering, Multidisciplinary

A watershed segmentation algorithm based on an optimal marker for bubble size measurement

Hu Zhang et al.

MEASUREMENT (2019)

Article Automation & Control Systems

Shape-weighted bubble size distribution based reagent predictive control for the antimony flotation process

Mingxi Ai et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2019)

Article Automation & Control Systems

Data-driven-based adaptive fuzzy neural network control for the antimony flotation plant

Mingxi Ai et al.

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS (2019)

Article Metallurgy & Metallurgical Engineering

Fault detection in flotation processes based on deep learning and support vector machine

Zhong-mei Li et al.

JOURNAL OF CENTRAL SOUTH UNIVERSITY (2019)

Article Computer Science, Information Systems

On-Line Froth Depth Estimation for Sulphur Flotation Process With Multiple Working Conditions

Mingfang He et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Clustering of Copper Flotation Process Based on the AP-GMM Algorithm

Zhiqiang Wang et al.

IEEE ACCESS (2019)

Article Engineering, Chemical

Data-driven flotation reagent changing evaluation via union distribution analysis of bubble size and shape

Mingxi Ai et al.

CANADIAN JOURNAL OF CHEMICAL ENGINEERING (2018)

Article Engineering, Chemical

A cascaded recognition method for copper rougher flotation working conditions

M. Lu et al.

CHEMICAL ENGINEERING SCIENCE (2018)

Article Engineering, Chemical

DTCWT-based zinc fast roughing working condition identification

Zhuo He et al.

CHINESE JOURNAL OF CHEMICAL ENGINEERING (2018)

Article Automation & Control Systems

Data-Driven Flotation Industrial Process Operational Optimal Control Based on Reinforcement Learning

Yi Jiang et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2018)

Article Metallurgy & Metallurgical Engineering

Relationship between froth bubble size estimates and flotation performance in a semi-batch lab cell

C. Bhondayi et al.

MINERAL PROCESSING AND EXTRACTIVE METALLURGY REVIEW (2018)

Article Engineering, Chemical

Froth image analysis by use of transfer learning and convolutional neural networks

Yihao Fu et al.

MINERALS ENGINEERING (2018)

Article Engineering, Chemical

Predicting flotation behaviour - The interaction between froth stability and performance

S. J. Neethling et al.

MINERALS ENGINEERING (2018)

Article Engineering, Chemical

Real-time monitoring of entrainment using fundamental models and froth images

Khushaal Popli et al.

MINERALS ENGINEERING (2018)

Article Engineering, Chemical

Considering the effect of pulp chemistry during flotation on froth stability

Nanji Sheni et al.

MINERALS ENGINEERING (2018)

Article Engineering, Chemical

Effect of froth rheology on froth and flotation performance

Chao Li et al.

MINERALS ENGINEERING (2018)

Article Metallurgy & Metallurgical Engineering

Relationship between froth bubble size estimates and flotation performance in a semi-batch lab cell

C. Bhondayi et al.

MINERAL PROCESSING AND EXTRACTIVE METALLURGY REVIEW (2018)

Article Multidisciplinary Sciences

Fuzzy Association Rule Based Froth Surface Behavior Control in Zinc Froth Flotation

Jin Zhang et al.

SYMMETRY-BASEL (2018)

Article Geochemistry & Geophysics

Froth Image Acquisition and Enhancement on Optical Correction and Retinex Compensation

Weixing Wang et al.

MINERALS (2018)

Article Engineering, Chemical

Effect of flotation conditions on froth rheology

Chao Li et al.

POWDER TECHNOLOGY (2018)

Proceedings Paper Automation & Control Systems

Adaptive fuzzy local ternary pattern for mineral flotation froth image edge detection

Kaijun Zhou et al.

IFAC PAPERSONLINE (2018)

Proceedings Paper Automation & Control Systems

Feature selection in froth flotation for production condition recognition

Qi'an Wang et al.

IFAC PAPERSONLINE (2018)

Proceedings Paper Automation & Control Systems

Using Convolutional Neural Networks to Develop State-of-the-Art Flotation Froth Image Sensors

Y. Fu et al.

IFAC PAPERSONLINE (2018)

Proceedings Paper Automation & Control Systems

Reagent Predictive Control Using Joint Froth Image Feature for Antimony Flotation Process

Mingxi Ai et al.

IFAC PAPERSONLINE (2018)

Article Engineering, Chemical

Development of a machine vision system for real-time monitoring and control of batch flotation process

A. Jahedsaravani et al.

INTERNATIONAL JOURNAL OF MINERAL PROCESSING (2017)

Article Engineering, Multidisciplinary

An image segmentation algorithm for measurement of flotation froth bubble size distributions

A. Jahedsaravani et al.

MEASUREMENT (2017)

Article Computer Science, Information Systems

Flotation froth image texture extraction method based on deterministic tourist walks

Jianqi Li et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2017)

Article Multidisciplinary Sciences

Mastering the game of Go without human knowledge

David Silver et al.

NATURE (2017)

Proceedings Paper Automation & Control Systems

Performance of Convolutional Neural Networks for Feature Extraction in Froth Flotation Sensing

Z. C. Horn et al.

IFAC PAPERSONLINE (2017)

Article Automation & Control Systems

Recognition of flooding and sinking conditions in flotation process using soft measurement of froth surface level and QTA

Lin Zhao et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2017)

Article Engineering, Chemical

Predictive control of the bubble size distribution in a two-phase pilot flotation column

A. Riquelme et al.

MINERALS ENGINEERING (2016)

Article Engineering, Chemical

The concentrate ash content analysis of coal flotation based on froth images

Jiakun Tan et al.

MINERALS ENGINEERING (2016)

Proceedings Paper Automation & Control Systems

Flotation Froth Image Analysis by Use of a Dynamic Feature Extraction Algorithm

Yihao Fu et al.

IFAC PAPERSONLINE (2016)

Article Computer Science, Artificial Intelligence

ImageNet Large Scale Visual Recognition Challenge

Olga Russakovsky et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2015)

Article Engineering, Chemical

An investigation into the relationship between particle shape and entrainment

J. Wiese et al.

MINERALS ENGINEERING (2015)

Article Engineering, Chemical

Hybrid model predictive control for flotation plants

Eduardo Putz et al.

MINERALS ENGINEERING (2015)

Article Engineering, Chemical

Modeling the Relationship between Froth Bubble Size and Flotation Performance Using Image Analysis and Neural Networks

M. R. Hosseini et al.

CHEMICAL ENGINEERING COMMUNICATIONS (2015)

Article Engineering, Chemical

Froth transport characterization in a two-dimensional flotation cell

I. Rojas et al.

MINERALS ENGINEERING (2014)

Article Computer Science, Artificial Intelligence

Machine Vision Based Production Condition Classification and Recognition for Mineral Flotation Process Monitoring

Jinping Liu et al.

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS (2013)

Article Engineering, Chemical

Color co-occurrence matrix based froth image texture extraction for mineral flotation

Weihua Gui et al.

MINERALS ENGINEERING (2013)

Article Engineering, Chemical

Integrated prediction model of bauxite concentrate grade based on distributed machine vision

Binfang Cao et al.

MINERALS ENGINEERING (2013)

Article Metallurgy & Metallurgical Engineering

Improved image enhancement method for flotation froth image based on parameter extraction

Li Jian-qi et al.

JOURNAL OF CENTRAL SOUTH UNIVERSITY (2013)

Article Engineering, Chemical

An investigation into the effect of water quality on froth stability

Saeed Farrokhpay et al.

ADVANCED POWDER TECHNOLOGY (2012)

Article Engineering, Chemical

The use of the froth surface lamellae burst rate as a flotation froth stability measurement

Sameer H. Morar et al.

MINERALS ENGINEERING (2012)

Review Chemistry, Physical

The significance of froth stability in mineral flotation - A review

Saeed Farrokhpay

ADVANCES IN COLLOID AND INTERFACE SCIENCE (2011)

Article Engineering, Chemical

Estimation of platinum flotation grades from froth image data

C. Marais et al.

MINERALS ENGINEERING (2011)

Review Engineering, Chemical

Online monitoring and control of froth flotation systems with machine vision: A review

C. Aldrich et al.

INTERNATIONAL JOURNAL OF MINERAL PROCESSING (2010)

Article Engineering, Chemical

Sericite-chalcocite mineral particle interactions and hetero-aggregation (sliming) mechanism in aqueous media

Mingzhao He et al.

CHEMICAL ENGINEERING SCIENCE (2009)

Article Engineering, Chemical

Quantifying contributions to froth stability in porphyry copper plants

M. Zanin et al.

INTERNATIONAL JOURNAL OF MINERAL PROCESSING (2009)

Article Engineering, Chemical

Dynamic froth stability: Particle size, airflow rate and conditioning time effects

Z. Aktas et al.

INTERNATIONAL JOURNAL OF MINERAL PROCESSING (2008)

Article Engineering, Chemical

PT Freeport Indonesia's mass-pull control strategy for rougher flotation

A. Supomo et al.

MINERALS ENGINEERING (2008)

Article Engineering, Chemical

Froth-based modeling and control of flotation processes

J. Jay Liu et al.

MINERALS ENGINEERING (2008)

Article Engineering, Chemical

Mechanism for the recovery of silicate gangue minerals in the flotation of ultrafine sphalerite

A. C. P. Duarte et al.

MINERALS ENGINEERING (2007)

Article Computer Science, Artificial Intelligence

One-shot learning of object categories

FF Li et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2006)

Article Engineering, Chemical

Development and application of an image analysis method for wide bubble size distributions

M Bailey et al.

MINERALS ENGINEERING (2005)

Article Engineering, Chemical

Flotation froth monitoring using multiresolutional multivariate image analysis

JJ Liu et al.

MINERALS ENGINEERING (2005)

Article Computer Science, Interdisciplinary Applications

Off-line image analysis for froth flotation of coal

C Citir et al.

COMPUTERS & CHEMICAL ENGINEERING (2004)

Article Engineering, Chemical

A study of bubble coalescence in flotation froths

S Ata et al.

INTERNATIONAL JOURNAL OF MINERAL PROCESSING (2003)

Article Computer Science, Interdisciplinary Applications

Characterisation of flotation froth colour and structure by machine vision

G Bonifazi et al.

COMPUTERS & GEOSCIENCES (2001)