Huaicheng Zhang

Orcid: 0000-0002-6874-5530

According to our database1, Huaicheng Zhang authored at least 12 papers between 2020 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
SIGxCL: A Signal-Image-Graph Cross-Modal Contrastive Learning Framework for CVD Diagnosis Based on Internet of Medical Things.
IEEE Internet Things J., April, 2024

ST-ReGE: A Novel Spatial-Temporal Residual Graph Convolutional Network for CVD.
IEEE J. Biomed. Health Informatics, January, 2024

Learning Representations for Multilead Electrocardiograms From Morphology-Rhythm Contrast.
IEEE Trans. Instrum. Meas., 2024

Honest-GE: 2-step heuristic optimization and node-level embedding empower spatial-temporal graph model for ECG.
Inf. Sci., 2024

An adaptive threshold-based semi-supervised learning method for cardiovascular disease detection.
Inf. Sci., 2024

DDDG: A dual bi-directional knowledge distillation method with generative self-supervised pre-training and its hardware implementation on SoC for ECG.
Expert Syst. Appl., 2024

CPSS: Fusing consistency regularization and pseudo-labeling techniques for semi-supervised deep cardiovascular disease detection using all unlabeled electrocardiograms.
Comput. Methods Programs Biomed., 2024

Universal 12-lead ECG representation for signal denoising and cardiovascular disease detection by fusing generative and contrastive learning.
Biomed. Signal Process. Control., 2024

2023
Dense lead contrast for self-supervised representation learning of multilead electrocardiograms.
Inf. Sci., July, 2023

MaeFE: Masked Autoencoders Family of Electrocardiogram for Self-Supervised Pretraining and Transfer Learning.
IEEE Trans. Instrum. Meas., 2023

A joint cross-dimensional contrastive learning framework for 12-lead ECGs and its heterogeneous deployment on SoC.
Comput. Biol. Medicine, 2023

2020
Intelligent Prediction and Optimization of Extraction Process Parameters for Paper-Making Reconstituted Tobacco.
Proceedings of the Bio-Inspired Computing: Theories and Applications, 2020


  Loading...