# Ukash Nakarmi

Orcid: 0000-0002-5351-3956
According to our database

Collaborative distances:

^{1}, Ukash Nakarmi authored at least 25 papers between 2011 and 2024.Collaborative distances:

## Timeline

#### Legend:

Book In proceedings Article PhD thesis Dataset Other## Links

#### On csauthors.net:

## Bibliography

2024

Adaptive Extensions of Unbiased Risk Estimators for Unsupervised Magnetic Resonance Image Denoising.

CoRR, 2024

Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials.

CoRR, 2024

Learning From Oversampling: A Systematic Exploitation of Oversampling to Address Data Scarcity Issues in Deep Learning- Based Magnetic Resonance Image Reconstruction.

IEEE Access, 2024

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2024

2023

When System Model Meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging.

Proceedings of the Advances in Visual Computing - 18th International Symposium, 2023

On Training Model Bias of Deep Learning based Super-resolution Frameworks for Magnetic Resonance Imaging.

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023

2022

Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case.

IEEE Trans. Computational Imaging, 2022

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

2020

IEEE Trans. Medical Imaging, 2020

Acceleration of three-dimensional diffusion magnetic resonance imaging using a kernel low-rank compressed sensing method.

NeuroImage, 2020

Spectral Decomposition in Deep Networks for Segmentation of Dynamic Medical Images.

CoRR, 2020

Multi-scale Unrolled Deep Learning Framework for Accelerated Magnetic Resonance Imaging.

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges.

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case.

Proceedings of the 28th European Signal Processing Conference, 2020

2019

IEEE Trans. Medical Imaging, 2019

2018

PhD thesis, 2018

MLS: Joint manifold-learning and sparsity-aware framework for highly accelerated dynamic magnetic resonance imaging.

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017

A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI.

IEEE Trans. Medical Imaging, 2017

M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging.

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016

Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

2015

Dynamic magnetic resonance imaging using compressed sensing with self-learned nonlinear dictionary (NL-D).

Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2012

Proceedings of the 31st IEEE Military Communications Conference, 2012

2011

Joint wideband spectrum sensing in frequency overlapping cognitive radio networks using distributed compressive sensing.

Proceedings of the MILCOM 2011, 2011