Sheng Chang

About Sheng Chang

Sheng Chang, With an exceptional h-index of 24 and a recent h-index of 20 (since 2020), a distinguished researcher at Wuhan University, specializes in the field of aritficial intelligence, nano device, integrated circuit.

His recent articles reflect a diverse array of research interests and contributions to the field:

Universal 12-lead ECG representation for signal denoising and cardiovascular disease detection by fusing generative and contrastive learning

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

面向小型边缘计算的深度可分离神经网络模型与硬件加速器设计.

Learning Representations for Multi-Lead Electrocardiograms from Morphology-Rhythm Contrast

A novel multiscale simulation framework for low-dimensional memristors

Optimized Solutions of Electrocardiogram Lead and Segment Selection for Cardiovascular Disease Diagnostics

First-Principles Prediction of Potential Candidate Materials ( = ) for Neuromorphic Computing

A Dynamic Pruning Method on Multiple Sparse Structures in Deep Neural Networks

Sheng Chang Information

University

Position

___

Citations(all)

1896

Citations(since 2020)

1483

Cited By

922

hIndex(all)

24

hIndex(since 2020)

20

i10Index(all)

52

i10Index(since 2020)

42

Email

University Profile Page

Google Scholar

Sheng Chang Skills & Research Interests

aritficial intelligence

nano device

integrated circuit

Top articles of Sheng Chang

Universal 12-lead ECG representation for signal denoising and cardiovascular disease detection by fusing generative and contrastive learning

Biomedical Signal Processing and Control

2024/8/1

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

Expert Systems with Applications

2024/6/15

面向小型边缘计算的深度可分离神经网络模型与硬件加速器设计.

Application Research of Computers/Jisuanji Yingyong Yanjiu

2024/3/1

Learning Representations for Multi-Lead Electrocardiograms from Morphology-Rhythm Contrast

IEEE Transactions on Instrumentation and Measurement

2024/2/23

A novel multiscale simulation framework for low-dimensional memristors

Science China Physics, Mechanics & Astronomy

2023/7

Optimized Solutions of Electrocardiogram Lead and Segment Selection for Cardiovascular Disease Diagnostics

Bioengineering

2023/5/18

First-Principles Prediction of Potential Candidate Materials ( = ) for Neuromorphic Computing

Physical Review Applied

2023/5/12

A Dynamic Pruning Method on Multiple Sparse Structures in Deep Neural Networks

IEEE Access

2023/4/17

A general quantum minimum searching algorithm with high success rate and its implementation

Science China Physics, Mechanics & Astronomy

2023/4

A fully-mapped and energy-efficient FPGA accelerator for dual-function AI-based analysis of ECG

Frontiers in Physiology

2023/2/6

A joint cross-dimensional contrastive learning framework for 12-lead ECGs and its heterogeneous deployment on SoC

Computers in Biology and Medicine

2023/1/1

Modulating Electrical Characteristics of ZnO Thin-Film Transistors by Scaling Down Gate Dielectric Thickness

IEEE Transactions on Electron Devices

2023/12/27

Engineering Atomic‐Scale Patterning and Resistive Switching in 2D Crystals and Application in Image Processing

Advanced Materials

2023/12

A Novel Interface Database of Graphene Nanoribbon from Density Functional Theory

arXiv preprint arXiv:2311.18203

2023/11/30

SIGxCL: A Signal-Image-Graph Cross-Modal Contrastive Learning Framework for CVD Diagnosis Based on Internet of Medical Things

IEEE Internet of Things Journal

2023/11/28

Graph machine learning framework for depicting wavefunction on interface

Machine Learning: Science and Technology

2023/11/27

Planar weibull quantum circuit genetic algorithm with strong search ability and its implementation

Physica Scripta

2023/11/22

ST-ReGE: A Novel Spatial-Temporal Residual Graph Convolutional Network for CVD

IEEE Journal of Biomedical and Health Informatics

2023/10/23

Micron Channel Length ZnO Thin Film Transistors with Different Gate Dielectric Thicknesses Based on Electronic Design Automation Tools

2023/8/25

Dense lead contrast for self-supervised representation learning of multilead electrocardiograms

Information Sciences

2023/7/1

See List of Professors in Sheng Chang University(Wuhan University)

Co-Authors

academic-engine