Lin Jiang

Orcid: 0000-0003-3149-2733

Affiliations:
  • Northeastern University, College of Information Science and Engineering, Shenyang, China


According to our database1, Lin Jiang authored at least 15 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Online Pipeline Weld Defect Detection for Magnetic Flux Leakage Inspection System via Lightweight Rotated Network.
IEEE Trans. Ind. Electron., July, 2025

Distributed Unsupervised Detection for Robust Power System False Data Attacks via Flexible Dynamic Time Warping Strategy.
IEEE Trans. Ind. Informatics, January, 2025

Double Coil Compensation Method for Reducing Distortion of High-Speed MFL Signals.
IEEE Trans. Instrum. Meas., 2025

A Novel Incremental Defect Detection Method via Elastic Heterogeneous Distillation Network.
IEEE Trans Autom. Sci. Eng., 2025

Mutual Supervision of MFL Heterogeneous Signals for Insufficient Sample Defect Detection on Pipeline Safety Operation.
IEEE Trans Autom. Sci. Eng., 2025

2024
A High-Precision Size Inversion Method for Pipeline Defects With the Influence of Velocity Effects.
IEEE Trans. Ind. Informatics, October, 2024

A Novel Weld Defect Detection Method for Intelligent Magnetic Flux Leakage Detection System via Contextual Relation Network.
IEEE Trans. Ind. Electron., June, 2024

A Physics-Guided MFL Deformed Defect Recovery Method.
IEEE Trans Autom. Sci. Eng., April, 2024

2023
SSCT-Net: A Semisupervised Circular Teacher Network for Defect Detection With Limited Labeled Multiview MFL Samples.
IEEE Trans. Ind. Informatics, October, 2023

An Intelligent Defect Detection Approach Based on Cascade Attention Network Under Complex Magnetic Flux Leakage Signals.
IEEE Trans. Ind. Electron., July, 2023

Pipeline Irregular Defect Inversion for Magnetic Flux Leakage Detection System Based on Heterogeneous Multiclass Feature Fusion.
IEEE Trans. Instrum. Meas., 2023

2022
THMS-Net: A Two-Stage Heterogeneous Signals Mutual Supervision Network for MFL Weak Defect Detection.
IEEE Trans. Instrum. Meas., 2022

A Multisensor Cycle-Supervised Convolutional Neural Network for Anomaly Detection on Magnetic Flux Leakage Signals.
IEEE Trans. Ind. Informatics, 2022

Anomaly detection of industrial multi-sensor signals based on enhanced spatiotemporal features.
Neural Comput. Appl., 2022

2021
Data Recovery of Magnetic Flux Leakage Data Gaps Using Multifeature Conditional Risk.
IEEE Trans Autom. Sci. Eng., 2021


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