Tao Zhang

Orcid: 0000-0003-4439-4892

Affiliations:
  • High Field Magnetic Resonance Brain Imaging Laboratory of Sichuan Province, Chengdu, China
  • University of Electronic Science and Technology of China, School of Life Science and Technology, Key Laboratory for NeuroInformation, Chengdu, China
  • Alltech Medical Systems, Chengdu, China (2012 - 2017)
  • Florida State University, Tallahassee, FL, USA (PhD 2004)


According to our database1, Tao Zhang authored at least 12 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Design and Optimization of a Novel Multi-Quadrant Spatial Array for Non-Invasive Focalized Magnetic Stimulation of the Deep Brain.
IEEE Access, 2024

2022
Single MR image super-resolution via channel splitting and serial fusion network.
Knowl. Based Syst., 2022

Enhancement of MRI-based Signal-to-Noise Ratio with Noise Scrambling.
Proceedings of the 9th International Conference on Biomedical and Bioinformatics Engineering, 2022

2021
MRI-Based Image Signal-to-Noise Ratio Enhancement with Different Receiving Gains in K-Space.
Sensors, 2021

2020
Gibbs-ringing artifact suppression with knowledge transfer from natural images to MR images.
Multim. Tools Appl., 2020

Accurate MR image super-resolution via lightweight lateral inhibition network.
Comput. Vis. Image Underst., 2020

2019
Channel Splitting Network for Single MR Image Super-Resolution.
IEEE Trans. Image Process., 2019

FC<sup>2</sup>N: Fully Channel-Concatenated Network for Single Image Super-Resolution.
CoRR, 2019

Single MR Image Super-Resolution via Channel Splitting and Serial Fusion Network.
CoRR, 2019

Automatic Windowing for MRI With Convolutional Neural Network.
IEEE Access, 2019

Experimental Verification of Human Body Communication Path Gain Channel Modeling for Muscular-Tissue Characteristics.
IEEE Access, 2019

2018
Multilevel Residual Learning for Single Image Super Resolution.
Proceedings of the Pattern Recognition and Computer Vision - First Chinese Conference, 2018


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