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An improved cell situation identification approach with convolutional neural network and wavelet extreme learning machine

Proceedings of the Institution of Mechanical Engineers. Part I, Journal of systems and control engineering, 2021-11, Vol.235 (10), p.1898-1905

2021

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Abnormality Monitoring in the Blast Furnace Ironmaking Process Based on Stacked Dynamic Target-Driven Denoising Autoencoders

IEEE transactions on industrial informatics, 2022-03, Vol.18 (3), p.1854-1863

2022

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ES-net: An Integration Model Based on Encoder-Decoder and Siamese Time Series Difference Network for Grade Monitoring of Zinc Tailings and Concentrate

IEEE transactions on industrial electronics (1982), 2023-11, Vol.70 (11), p.11819-11830

2023

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Label Propagation With Contrastive Anchors for Deep Semi-Supervised Superheat Degree Identification in Aluminum Electrolysis Process

IEEE transactions on automation science and engineering, 2024-04, Vol.21 (2), p.1-13

2024

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A Projective and Discriminative Dictionary Learning for High-Dimensional Process Monitoring With Industrial Applications

IEEE transactions on industrial informatics, 2021-01, Vol.17 (1), p.558-568

2021

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Sensitive Feature Selection for Industrial Flotation Process Soft Sensor Based on Multiswarm PSO With Collaborative Search

IEEE sensors journal, 2024-05, Vol.24 (10), p.17159-17168

2024

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Temperature Measurement and Compensation Method of Blast Furnace Molten Iron Based on Infrared Computer Vision

IEEE transactions on instrumentation and measurement, 2019-10, Vol.68 (10), p.3576-3588

2019

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LTGH: A Dynamic Texture Feature for Working Condition Recognition in the Froth Flotation

IEEE transactions on instrumentation and measurement, 2021, Vol.70, p.1-10

2021

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Measurement of Froth-Layer Depth With Binocular Camera Based on Intensity Correction and Its Application to Pulp-Grade Monitoring

IEEE transactions on instrumentation and measurement, 2024, Vol.73, p.1-9

2024

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Operating Condition Recognition in Zinc Flotation Using Statistic and Temporal Correlation Features

IEEE transactions on instrumentation and measurement, 2022, Vol.71, p.1-12

2022

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A Cooperative Silicon Content Dynamic Prediction Method with Variable Time Delay Estimation in the Blast Furnace Ironmaking Process

IEEE transactions on industrial informatics, 2024-01, Vol.20 (1), p.1-12

2024

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

IEEE transactions on instrumentation and measurement, 2021, Vol.70, p.1-14

2021

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Memory Shapelet Learning for Early Classification of Streaming Time Series

IEEE transactions on cybernetics, 2024-05, Vol.54 (5), p.2757-2770

2024

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Siamese Time Series and Difference Networks for Performance Monitoring in the Froth Flotation Process

IEEE transactions on industrial informatics, 2022-04, Vol.18 (4), p.2539-2549

2022

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

Chemometrics and intelligent laboratory systems, 2019-09, Vol.192, p.103821, Article 103821

2019

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Feature Reconstruction-Regression Network: A Light-Weight Deep Neural Network for Performance Monitoring in the Froth Flotation

IEEE transactions on industrial informatics, 2021-12, Vol.17 (12), p.8406-8417

2021

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RPI-SURF: A Feature Descriptor for Bubble Velocity Measurement in Froth Flotation With Relative Position Information

IEEE transactions on instrumentation and measurement, 2021, Vol.70, p.1-14

2021

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Dual-Rule-Based Weighted Fuzzy Interpolative Reasoning Module and Temporal Encoder-Decoder Bayesian Network for Reagent Addition Control

IEEE transactions on fuzzy systems, 2024-07, Vol.32 (7), p.3891-3902

2024

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Domain Knowledge Distillation and Supervised Contrastive Learning for Industrial Process Monitoring

IEEE transactions on industrial electronics (1982), 2023-09, Vol.70 (9), p.9452-9462

2023

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A Binocular Camera Calibration Method in Froth Flotation Based on Key Frame Sequences and Weighted Normalized Tilt Difference

IEEE transactions on circuits and systems for video technology, 2023-10, Vol.33 (10), p.1-1

2023

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Velocity Measurement of Blast Furnace Molten Iron Based on Mixed Morphological Features of Boundary Pixel Sets

IEEE transactions on instrumentation and measurement, 2021, Vol.70, p.1-12

2021

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Grouped Time Series Networks for Grade Monitoring of Zinc Tailings With Multisource Features

IEEE transactions on instrumentation and measurement, 2021, Vol.70, p.1-11

2021

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Velocity Measurement of Blast Furnace Molten Iron Based on Local Multi-Feature Correction Using Multi-Stage Filtered High-Speed Camera

IEEE sensors journal, 2020-10, Vol.20 (19), p.11537-11548

2020

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Design of Soft Sensor for Industrial Antimony Flotation Based on Deep CNN

2020 Chinese Control And Decision Conference (CCDC), 2020, p.2492-2496

2020

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Adversarial Training-Based Deep Layer-Wise Probabilistic Network for Enhancing Soft Sensor Modeling of Industrial Processes

IEEE transactions on systems, man, and cybernetics. Systems, 2024-02, Vol.54 (2), p.1-13

2024

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An improved cell situation identification approach with convolutional neural network and wavelet extreme learning machine

Abnormality Monitoring in the Blast Furnace Ironmaking Process Based on Stacked Dynamic Target-Driven Denoising Autoencoders

ES-net: An Integration Model Based on Encoder-Decoder and Siamese Time Series Difference Network for Grade Monitoring of Zinc Tailings and Concentrate

Label Propagation With Contrastive Anchors for Deep Semi-Supervised Superheat Degree Identification in Aluminum Electrolysis Process

A Projective and Discriminative Dictionary Learning for High-Dimensional Process Monitoring With Industrial Applications

Sensitive Feature Selection for Industrial Flotation Process Soft Sensor Based on Multiswarm PSO With Collaborative Search

Temperature Measurement and Compensation Method of Blast Furnace Molten Iron Based on Infrared Computer Vision

LTGH: A Dynamic Texture Feature for Working Condition Recognition in the Froth Flotation

Measurement of Froth-Layer Depth With Binocular Camera Based on Intensity Correction and Its Application to Pulp-Grade Monitoring

Operating Condition Recognition in Zinc Flotation Using Statistic and Temporal Correlation Features

A Cooperative Silicon Content Dynamic Prediction Method with Variable Time Delay Estimation in the Blast Furnace Ironmaking Process

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

Memory Shapelet Learning for Early Classification of Streaming Time Series

Siamese Time Series and Difference Networks for Performance Monitoring in the Froth Flotation Process

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

Feature Reconstruction-Regression Network: A Light-Weight Deep Neural Network for Performance Monitoring in the Froth Flotation

RPI-SURF: A Feature Descriptor for Bubble Velocity Measurement in Froth Flotation With Relative Position Information

Dual-Rule-Based Weighted Fuzzy Interpolative Reasoning Module and Temporal Encoder-Decoder Bayesian Network for Reagent Addition Control

Domain Knowledge Distillation and Supervised Contrastive Learning for Industrial Process Monitoring

A Binocular Camera Calibration Method in Froth Flotation Based on Key Frame Sequences and Weighted Normalized Tilt Difference

Velocity Measurement of Blast Furnace Molten Iron Based on Mixed Morphological Features of Boundary Pixel Sets

Grouped Time Series Networks for Grade Monitoring of Zinc Tailings With Multisource Features

Velocity Measurement of Blast Furnace Molten Iron Based on Local Multi-Feature Correction Using Multi-Stage Filtered High-Speed Camera

Design of Soft Sensor for Industrial Antimony Flotation Based on Deep CNN

Adversarial Training-Based Deep Layer-Wise Probabilistic Network for Enhancing Soft Sensor Modeling of Industrial Processes

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