activity
20212024
most citedA Learning-Based 3D EIT Image Reconstruction Method

4 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO20241 cited

Closed-loop underwater soft robotic foil shape control using flexible e-skin

Leo Micklem, Huazhi Dong, Francesco Giorgio-Serchi +3

The use of soft robotics for real-world underwater applications is limited, even more than in terrestrial applications, by the ability to accurately measure and control the deforma…

cs.RO2023

Touch and deformation perception of soft manipulators with capacitive e-skins and deep learning

Delin Hu, Zhou Chen, Paul Baisamy +3

Tactile sensing in soft robots remains particularly challenging because of the coupling between contact and deformation information which the sensor is subject to during actuation…

eess.IV20231 cited

Regularized Shallow Image Prior for Electrical Impedance Tomography

Zhe Liu, Zhou Chen, Qi Wang +2

Untrained Neural Network Prior (UNNP) based algorithms have gained increasing popularity in tomographic imaging, as they offer superior performance compared to hand-crafted priors…

eess.IV20224 cited

A Learning-Based 3D EIT Image Reconstruction Method

Zhaoguang Yi, Zhou Chen, Yunjie Yang

Deep learning has been widely employed to solve the Electrical Impedance Tomography (EIT) image reconstruction problem. Most existing physical model-based and learning-based approa…

physics.flu-dyn2021

Digital Twin of Electrical Tomography for Quantitative Multiphase Flow Imaging

Shengnan Wang, Delin Hu, Maomao Zhang +6

We report a digital twin (DT) framework of electrical tomography (ET) to address the challenge of real-time quantitative multiphase flow imaging based on non-invasive and non-radio…