Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Bioactive Electrode System With External Connectivity for Electrically Augmented Bone Regeneration.

Advanced healthcare materials·2026

Same author

3D-printed chitosan-based hydrogel scaffold doped with curcumin-loaded quantum dots enables photothermal effect and degradation visualization for bone regeneration.

Carbohydrate polymers·2026

Same author

An evidence-based nursing management app prototype for adult urology day surgery: an AI-driven development pathway.

BMC nursing·2026

Same author

NSUN2/ALYREF stabilizes m5C-modified circCEP70 to enhance radioresistance in rectal cancer through NEDD8-dependent neddylation and ubiquitination regulation.

International journal of biological macromolecules·2026

Same author

O-O hemi-bonding in cationic water clusters: Benchmarks from DFT, PNO-LCCSD(T), and FN-DMC.

The Journal of chemical physics·2026

Same author

Population pharmacokinetic modeling and Monte Carlo simulation-based dosing optimization of trimethoprim-sulfamethoxazole in critically ill patients.

European journal of clinical pharmacology·2026

Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026

Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026

Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026

Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026

Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026

Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 10, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Deep Learning Based Feature Selection and Ensemble Learning for Sintering State Recognition.

Xinran Xu¹, Xiaojun Zhou²

¹School of Computer Science and Engineering, Central South University, Changsha 410083, China.

Sensors (Basel, Switzerland)

|November 25, 2023

Summary

This summary is machine-generated.

This study introduces a novel deep learning method for recognizing iron ore sintering quality. The approach uses infrared imaging and ensemble learning to improve blast furnace efficiency.

Keywords:

binary state transition algorithm deep learning ensemble learning feature selection group decision making sintering state

More Related Videos

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Jul 10, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Area of Science:

Metallurgical Engineering
Artificial Intelligence

Background:

Sintering is crucial for blast furnace ironmaking, but quality assessment relies on subjective operator observation.
Current methods are inconsistent due to environmental factors and operator experience.

Purpose of the Study:

To develop an automated, objective method for recognizing sintering quality.
To enhance the efficiency and reliability of the blast furnace ironmaking process.

Main Methods:

Utilized deep learning (ResNeXt) for feature extraction from infrared thermal images of sinter cross-sections.
Implemented a binary state transition algorithm (BSTA) for efficient feature selection.
Employed ensemble learning (EL) with group decision making (GDM) and novel combination strategies for state recognition.

Main Results:

The proposed deep learning and ensemble learning method achieved superior recognition accuracy for sintering states.
Industrial experiments confirmed the effectiveness and advantages of the developed technique.

Conclusions:

The new method offers an objective and accurate approach to sintering quality assessment.
This advancement can significantly improve blast furnace operations and iron production.