Ukash Nakarmi - RankMe

32 papers Journal 13Unranked 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Efficient Back-Projection Technique for Multiple Objects Detection and 2D Imaging Through Photonics-Based LFM Radar. IEEE Access T. D. Subash, Sun Zhijie, Mohd Rashidi Che Beson, S. M. Rezwanul Islam, Ukash Nakarmi, Ikechi Augustine Ukaegbu, Bikash Nakarmi
2025	—	`conf`	From Noise Estimation to Restoration: A Unified Diffusion and Bayesian Risk Approach for Unsupervised Denoising. VISIGRAPP (3): VISAPP Reeshad Khan, Ukash Nakarmi, John M. Gauch
2024	J	`jnl`	Adaptive Extensions of Unbiased Risk Estimators for Unsupervised Magnetic Resonance Image Denoising. CoRR Reeshad Khan, John Gauch, Ukash Nakarmi
2024	—	`conf`	Cut-Puzzle mix: Scribble Guided Medical Image Segmentation without Segmentation Masks. EMBC Ibsa Jalata, Ukash Nakarmi
2024	—	`conf`	DeepLIR: Attention-Based Approach for Mask-Based Lensless Image Reconstruction. WACV (Workshops) Arpan Poudel, Ukash Nakarmi
2024	J	`jnl`	Learning From Oversampling: A Systematic Exploitation of Oversampling to Address Data Scarcity Issues in Deep Learning- Based Magnetic Resonance Image Reconstruction. IEEE Access Ibsa Jalata, Reeshad Khan, Ukash Nakarmi
2024	—	`conf`	Semi-Supervised Medical Image Segmentation using Puzzlemix Augmentation Technique. BIBM Ibsa Jalata, Ukash Nakarmi
2024	J	`jnl`	Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials. CoRR Shakil Rafi, Joshua Lee Padgett, Ukash Nakarmi
2023	—	`conf`	On Training Model Bias of Deep Learning based Super-resolution Frameworks for Magnetic Resonance Imaging. BHI Mamata Shrestha, Nian Wang, Ukash Nakarmi
2023	—	`conf`	When System Model Meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging. ISVC (1) Ibsa Jalata, Ukash Nakarmi
2022	—	`conf`	BrainVGAE: End-to-End Graph Neural Networks for Noisy fMRI Dataset. BIBM Quan Mai, Ukash Nakarmi, Miaoqing Huang
2022	J	`jnl`	Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case. IEEE Trans. Computational Imaging Konstantinos Slavakis, Gaurav N. Shetty, Loris Cannelli, Gesualdo Scutari, Ukash Nakarmi, Leslie Ying
2021	—	`conf`	Parallel MRI Reconstruction Using Broad Learning System. EMBC Yuchou Chang, Ukash Nakarmi
2020	J	`jnl`	Acceleration of three-dimensional diffusion magnetic resonance imaging using a kernel low-rank compressed sensing method. NeuroImage Chaoyi Zhang, Tanzil Mahmud Arefin, Ukash Nakarmi, Choong-Heon Lee, Hongyu Li, Dong Liang, Jiangyang Zhang, Leslie Ying
2020	J	`jnl`	Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. IEEE Trans. Medical Imaging Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying
2020	—	`conf`	Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges. ISBI Jeffrey J. Ma, Ukash Nakarmi, Cedric Yue Sik Kin, Christopher M. Sandino, Joseph Y. Cheng, Ali B. Syed, Peter Wei, John M. Pauly, Shreyas S. Vasanawala
2020	—	`conf`	Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case. EUSIPCO Gaurav N. Shetty, Konstantinos Slavakis, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying
2020	J	`jnl`	Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case. CoRR Gaurav N. Shetty, Konstantinos Slavakis, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying
2020	—	`conf`	Multi-scale Unrolled Deep Learning Framework for Accelerated Magnetic Resonance Imaging. ISBI Ukash Nakarmi, Joseph Y. Cheng, Edgar P. Rios, Morteza Mardani, John M. Pauly, Leslie Ying, Shreyas S. Vasanawala
2020	J	`jnl`	Spectral Decomposition in Deep Networks for Segmentation of Dynamic Medical Images. CoRR Edgar A. Rios Piedra, Morteza Mardani, Frank Ong, Ukash Nakarmi, Joseph Y. Cheng, Shreyas Vasanawala
2019	J	`jnl`	Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges. CoRR Jeffrey J. Ma, Ukash Nakarmi, Cedric Yue Sik Kin, Christopher M. Sandino, Joseph Y. Cheng, Ali B. Syed, Peter Wei, John M. Pauly, Shreyas Vasanawala
2019	J	`jnl`	KerNL: Kernel-Based Nonlinear Approach to Parallel MRI Reconstruction. IEEE Trans. Medical Imaging Jingyuan Lyu, Ukash Nakarmi, Dong Liang, Jinhua Sheng, Leslie Ying
2018	J	`jnl`	Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. CoRR Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Leslie Ying, Gesualdo Scutari
2018	—	`—`	Kernel and Manifold Framework for Magnetic Resonance Imaging. Ukash Nakarmi
2018	—	`conf`	MLS: Joint manifold-learning and sparsity-aware framework for highly accelerated dynamic magnetic resonance imaging. ISBI Ukash Nakarmi, Konstantinos Slavakis, Leslie Ying
2017	J	`jnl`	A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI. IEEE Trans. Medical Imaging Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu, Dong Liang, Leslie Ying
2017	—	`conf`	Bi-Linear modeling of manifold-data geometry for Dynamic-MRI recovery. CAMSAP Konstantinos Slavakis, Gaurav N. Shetty, Abhishek Bose, Ukash Nakarmi, Leslie Ying
2017	—	`conf`	M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging. ISBI Ukash Nakarmi, Konstantinos Slavakis, Jingyuan Lyu, Leslie Ying
2016	—	`conf`	Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding. ISBI Ukash Nakarmi, Yihang Zhou, Jingyuan Lyu, Konstantinos Slavakis, Leslie Ying
2015	—	`conf`	Dynamic magnetic resonance imaging using compressed sensing with self-learned nonlinear dictionary (NL-D). ISBI Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu, Leslie Ying
2012	—	`conf`	BCS: Compressive sensing for binary sparse signals. MILCOM Ukash Nakarmi, Nazanin Rahnavard
2011	—	`conf`	Joint wideband spectrum sensing in frequency overlapping cognitive radio networks using distributed compressive sensing. MILCOM Ukash Nakarmi, Nazanin Rahnavard