Zhiyuan Li

Orcid: 0000-0003-1323-6795

Affiliations:
  • Shanghai Jiao Tong University, School of Mechanical Engineering, MoE Key Lab of Artificial Intelligence, AI Institute, China


According to our database1, Zhiyuan Li authored at least 24 papers between 2021 and 2025.

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

Timeline

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Bibliography

2025
MM-Tracker: Visual Tracking With A Multi-Task Model Integrating Detection and Differentiating Feature Extraction.
IEEE Trans. Emerg. Top. Comput. Intell., August, 2025

EDDM: A Novel ECG Denoising Method Using Dual-Path Diffusion Model.
IEEE Trans. Instrum. Meas., 2025

An early warning method for arrhythmias in long-term ECGs based on self-supervised learning and LSTM.
Knowl. Based Syst., 2025

BioCross: A cross-modal framework for unified representation of multi-modal biosignals with heterogeneous metadata fusion.
Inf. Fusion, 2025

Multi-task learning for multi-label electrocardiogram disease detection via point-level delineation-guided fusion.
Eng. Appl. Artif. Intell., 2025

2024
A novel deep wavelet convolutional neural network for actual ECG signal denoising.
Biomed. Signal Process. Control., January, 2024

Lightweight Optimization of Deep Learning Models for Accurate Arrhythmia Detection in Clinical 12-Lead ECG Data.
IEEE Trans. Instrum. Meas., 2024

Differentiated knowledge distillation: Patient-specific single-sample personalization for electrocardiogram diagnostic models.
Eng. Appl. Artif. Intell., 2024

M-XAF: Medical explainable diagnosis system of atrial fibrillation based on medical knowledge and semantic representation fusion.
Eng. Appl. Artif. Intell., 2024

Automatic multi-label diagnosis of single-lead ECG using novel hybrid residual recurrent convolutional neural networks.
Biomed. Signal Process. Control., 2024

Pruned lightweight neural networks for arrhythmia classification with clinical 12-Lead ECGs.
Appl. Soft Comput., 2024

A self-supervised framework for computer-aided arrhythmia diagnosis.
Appl. Soft Comput., 2024

2023
A deep learning-based acute coronary syndrome-related disease classification method: a cohort study for network interpretability and transfer learning.
Appl. Intell., November, 2023

Multiple Pedestrian Tracking With Graph Attention Map on Urban Road Scene.
IEEE Trans. Intell. Transp. Syst., August, 2023

A novel attentional deep neural network-based assessment method for ECG quality.
Biomed. Signal Process. Control., 2023

An Interpretable Residual Neural Network for the Diagnosis of Myocardial Infarction.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023

Interpretable Deep Learning Model for Identifying the Immediate Risk of Myocardial Infarction Complications.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023

Evaluate the Correlation Between Electrocardiogram Age and Cardiovascular Disease Using a 12-lead ECG Dataset.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023

A Novel Personalized Incremental Arrhythmias Classification Method for ECG Monitoring.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023

ECG Quality Assessment Framework by Using Attentional Convolution Neural Network.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023

2022
A Novel Interpretable Method Based on Dual-Level Attentional Deep Neural Network for Actual Multilabel Arrhythmia Detection.
IEEE Trans. Instrum. Meas., 2022

An efficient neural network-based method for patient-specific information involved arrhythmia detection.
Knowl. Based Syst., 2022

A novel P-QRS-T wave localization method in ECG signals based on hybrid neural networks.
Comput. Biol. Medicine, 2022

2021
A Novel Incremental and Interactive Method for Actual Heartbeat Classification With Limited Additional Labeled Samples.
IEEE Trans. Instrum. Meas., 2021


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