Zhichao Lin

About Zhichao Lin

Zhichao Lin, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at Tsinghua University, specializes in the field of Deep Learning, Inverse Scattering, Electrical Impedance Tomography.

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

Recent Advances in Multiscale-Multiphysics Inverse Scattering

Three Dimensional Microwave Data Inversion in Feature Space for Stroke Imaging

Physics Embedded Weight-Sharing Neural Network for Electrical Impedance Tomography

Artificial Intelligence for EM Imaging: Recent Advances and Future Trends

Spatio-temporal classification of lung ventilation patterns using 3d eit images: A general approach for individualized lung function evaluation

Tri-modal Joint Inversion Based on Disentangled Variational Autoencoder for Human Thorax Imaging

Multi-Resolution Multi-Physics Imaging of Free-Space Targets

Joint inversion of electrical impedance, microwave and ultrasonic data with structural feature fusion for human thorax imaging

Zhichao Lin Information

University

Position

___

Citations(all)

211

Citations(since 2020)

211

Cited By

5

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Zhichao Lin Skills & Research Interests

Deep Learning

Inverse Scattering

Electrical Impedance Tomography

Top articles of Zhichao Lin

Recent Advances in Multiscale-Multiphysics Inverse Scattering

2024/3/17

Three Dimensional Microwave Data Inversion in Feature Space for Stroke Imaging

IEEE Transactions on Medical Imaging

2023/11/28

Physics Embedded Weight-Sharing Neural Network for Electrical Impedance Tomography

2023/11/15

Artificial Intelligence for EM Imaging: Recent Advances and Future Trends

2023/11/15

Spatio-temporal classification of lung ventilation patterns using 3d eit images: A general approach for individualized lung function evaluation

IEEE Journal of Biomedical and Health Informatics

2023/10/30

Tri-modal Joint Inversion Based on Disentangled Variational Autoencoder for Human Thorax Imaging

IEEE Transactions on Instrumentation and Measurement

2023/9/25

Multi-Resolution Multi-Physics Imaging of Free-Space Targets

2023/7/23

Joint inversion of electrical impedance, microwave and ultrasonic data with structural feature fusion for human thorax imaging

2023/6/28

Recent Advances in IMSA for Electromagnetic Inverse Problems

2023/3/26

Physics-informed supervised residual learning for 2-D inverse scattering problems

IEEE Transactions on Antennas and Propagation

2023/2/9

Analysis of Degrees of Freedom in Scattered Fields for Nonlinear Inverse Scattering Problems

arXiv preprint arXiv:2212.08903

2022/12/17

A deep generative model-integrated framework for 3-D time-difference electrical impedance tomography

IEEE Transactions on Instrumentation and Measurement

2022/12/8

Neural born iterative method for solving inverse scattering problems: 2D cases

IEEE Transactions on Antennas and Propagation

2022/11/1

A nonlinear model compression scheme based on variational autoencoder for microwave data inversion

IEEE Transactions on Antennas and Propagation

2022/8/8

Feature-based inversion using variational autoencoder for electrical impedance tomography

IEEE Transactions on Instrumentation and Measurement

2022/7/18

Microwave Data Inversion With a Model Compression Scheme Based on Deep Learning

2022/7/10

A new approach for solving inverse scattering problems based on physics-informed supervised residual learning

2022/3/27

Low-Frequency Data Learning for Solving Highly Nonlinear Inverse Scattering Problems

2022/3/27

Feature-Based Model Compression Scheme for Electrical Impedance Tomography.

International Journal of Bioelectromagnetism

2022/1/2

Study on the degrees of freedom of scattered fields in nonlinear inverse scattering problems

2021/12/4

See List of Professors in Zhichao Lin University(Tsinghua University)

Co-Authors

academic-engine