Yongqiang Huang

Affiliations:
  • Sichuan University, College of Computer Science, Chengdu, China


According to our database1, Yongqiang Huang authored at least 12 papers between 2020 and 2023.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
M<sub>3</sub>NAS: Multi-Scale and Multi-Level Memory-Efficient Neural Architecture Search for Low-Dose CT Denoising.
IEEE Trans. Medical Imaging, March, 2023

2022
Low-Dose CT Denoising via Neural Architecture Search.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021
MAGIC: Manifold and Graph Integrative Convolutional Network for Low-Dose CT Reconstruction.
IEEE Trans. Medical Imaging, 2021

CT Reconstruction With PDF: Parameter-Dependent Framework for Data From Multiple Geometries and Dose Levels.
IEEE Trans. Medical Imaging, 2021

Noise-Powered Disentangled Representation for Unsupervised Speckle Reduction of Optical Coherence Tomography Images.
IEEE Trans. Medical Imaging, 2021

MANAS: Multi-Scale and Multi-Level Neural Architecture Search for Low-Dose CT Denoising.
CoRR, 2021

DAN-Net: Dual-Domain Adaptive-Scaling Non-local Network for CT Metal Artifact Reduction.
CoRR, 2021

One Network to Solve Them All: A Sequential Multi-task Joint Learning Network Framework for MR Imaging Pipeline.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2021

Dual-Domain Adaptive-Scaling Non-local Network for CT Metal Artifact Reduction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Ct Reconstruction With Pdf: Parameter-Dependent Framework For Multiple Scanning Geometries And Dose Levels.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

2020
CT Reconstruction with PDF: Parameter-Dependent Framework for Multiple Scanning Geometries and Dose Levels.
CoRR, 2020

Disentanglement Network for Unsupervised Speckle Reduction of Optical Coherence Tomography Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020


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