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Zicheng Liu

4 papers hereh-index 14 citations16 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • eess.IV1
  • physics.app-ph1
  • physics.comp-ph1
same name
  • Zicheng Liu — 91 papers, h 51
  • Zicheng Liu — 37 papers, h 11
  • Zicheng Liu — 27 papers, h 18
  • Zicheng Liu — 17 papers, h 14
  • Zicheng Liu — 6 papers, h 7
  • Zicheng Liu — 3 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedQuality-factor inspired deep neural network solver for solving inverse scattering problems

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2026

Structured Multi-Level-Set Inversion for 3-D Electromagnetic Inverse Scattering

Yutong Du, Zicheng Liu, Bo Qi +3

Many dielectric targets encountered in 3-D electromagnetic inverse scattering exhibit piecewise-homogeneous material distributions, which provide useful structural information for…

physics.comp-ph2026

Coordinate-Residual Physics-Driven Neural Network for Inverse Scattering Imaging

Yutong Du, Zicheng Liu, Bo Qi +2

Electromagnetic inverse scattering is a nonlinear and ill-posed computational imaging problem, where accurate reconstruction is challenging due to measurement limitations, noise, a…

physics.app-ph2025

Field Reconstruction for High-Frequency Electromagnetic Exposure Assessment Based on Deep Learning

Miao Cao, Zicheng Liu, Bazargul Matkerim +4

Fifth-generation (5G) communication systems, operating in higher frequency bands from 3 to 300 GHz, provide unprecedented bandwidth to enable ultra-high data rates and low-latency…

eess.IV2025★ 1 cited

Quality-factor inspired deep neural network solver for solving inverse scattering problems

Yutong Du, Zicheng Liu, Miao Cao +3

Deep neural networks have been applied to address electromagnetic inverse scattering problems (ISPs) and shown superior imaging performances, which can be affected by the training…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.