Hang Zhang

Orcid: 0000-0003-0115-387X

Affiliations:
  • Cornell University, School of Electrical and Computer Engineering, Ithaca, NY, USA
  • Chinese University of Hong Kong, Department of Computer Science and Engineering, Hong Kong (former)


According to our database1, Hang Zhang authored at least 23 papers between 2016 and 2023.

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Bibliography

2023
LARO: Learned acquisition and reconstruction optimization to accelerate quantitative susceptibility mapping.
NeuroImage, March, 2023

2021
Motion Artifact Reduction in Quantitative Susceptibility Mapping using Deep Neural Network.
CoRR, 2021

NeRD: Neural Representation of Distribution for Medical Image Segmentation.
CoRR, 2021

Ensembling Low Precision Models for Binary Biomedical Image Segmentation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Hybrid optimization between iterative and network fine-tuning reconstructions for fast quantitative susceptibility mapping.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Geometric Loss For Deep Multiple Sclerosis Lesion Segmentation.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Efficient Folded Attention for Medical Image Reconstruction and Segmentation.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction.
NeuroImage, 2020

Efficient Folded Attention for 3D Medical Image Reconstruction and Segmentation.
CoRR, 2020

Bayesian Learning of Probabilistic Dipole Inversion for Quantitative Susceptibility Mapping.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Extending LOUPE for K-Space Under-Sampling Pattern Optimization in Multi-coil MRI.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2020

Neural-ILT: Migrating ILT to Neural Networks for Mask Printability and Complexity Co-optimization.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

2019
RSANet: Recurrent Slice-Wise Attention Network for Multiple Sclerosis Lesion Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

A fast machine learning-based mask printability predictor for OPC acceleration.
Proceedings of the 24th Asia and South Pacific Design Automation Conference, 2019

2018
A New Regularized Matrix Discriminant Analysis (R-MDA) Enabled Human-Centered EEG Monitoring Systems.
IEEE Access, 2018

Fast and Accurate Estimation of Quality of Results in High-Level Synthesis with Machine Learning.
Proceedings of the 26th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2018

2017
Bilinear Lithography Hotspot Detection.
Proceedings of the 2017 ACM on International Symposium on Physical Design, 2017

Minimizing Thermal Gradient and Pumping Power in 3D IC Liquid Cooling Network Design.
Proceedings of the 54th Annual Design Automation Conference, 2017

2016
Robust Matrix Regression.
CoRR, 2016

Enabling online learning in lithography hotspot detection with information-theoretic feature optimization.
Proceedings of the 35th International Conference on Computer-Aided Design, 2016

RippleFPGA: a routability-driven placement for large-scale heterogeneous FPGAs.
Proceedings of the 35th International Conference on Computer-Aided Design, 2016

VLSI layout hotspot detection based on discriminative feature extraction.
Proceedings of the 2016 IEEE Asia Pacific Conference on Circuits and Systems, 2016


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