Burhaneddin Yaman

According to our database1, Burhaneddin Yaman authored at least 11 papers between 2017 and 2020.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
Low-Rank Tensor Models for Improved Multidimensional MRI: Application to Dynamic Cardiac T<sub>1</sub> Mapping.
IEEE Trans. Computational Imaging, 2020

Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms.
IEEE J. Sel. Top. Signal Process., 2020

Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI.
CoRR, 2020

Noise2Inpaint: Learning Referenceless Denoising by Inpainting Unrolling.
CoRR, 2020

Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Scan-Specific Accelerated Mri Reconstruction Using Recurrent Neural Networks In A Regularized Self-Consistent Framework.
Proceedings of the 2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops), 2020

High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

2019
Self-Supervised Learning of Physics-Based Reconstruction Neural Networks without Fully-Sampled Reference Data.
CoRR, 2019

Dense Recurrent Neural Networks for Inverse Problems: History-Cognizant Unrolling of Optimization Algorithms.
CoRR, 2019

2017
Unified outage performance analysis of two-way/one-way full-duplex/half-duplex fixed-gain AF relay systems.
Proceedings of the 24th International Conference on Telecommunications, 2017

Locally Low-Rank tensor regularization for high-resolution quantitative dynamic MRI.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017


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