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2020 – today
- 2024
[c46]Chi Zhang, Mehmet Akçakaya:
Uncertainty-Guided Physics-Driven Deep Learning Reconstruction via Cyclic Measurement Consistency. ICASSP 2024: 13441-13445- [c45]Yasar Utku Alçalar, Merve Gülle, Mehmet Akçakaya:
A Convex Compressibility-Inspired Unsupervised Loss Function for Physics-Driven Deep Learning Reconstruction. ISBI 2024: 1-5 - [c44]Hongyi Gu, Chi Zhang, Zidan Yu, Christoph Rettenmeier, V. Andrew Stenger, Mehmet Akçakaya:
Non-Cartesian Self-Supervised Physics-Driven Deep Learning Reconstruction for Highly-Accelerated Multi-Echo Spiral fMRI. ISBI 2024: 1-5 - [c43]Merve Gülle, Mehmet Akçakaya:
Robust Outer Volume Subtraction with Deep Learning Ghosting Detection for Highly-Accelerated Real-Time Dynamic MRI. ISBI 2024: 1-5 - [c42]Toygan Kilic, Jürgen Herrler, Patrick Liebig, Ömer Burak Demirel, Armin M. Nagel, Mingyi Hong, Georgios B. Giannakis, Kâmil Ugurbil, Mehmet Akçakaya:
Towards Fast Hard-Constrained Parallel Transmit Design in Ultrahigh Field MRI with Physics-Driven Neural Networks. ISBI 2024: 1-5 - [c41]Chi Zhang, Omer Burak Demirel, Mehmet Akçakaya:
Cycle-Consistent Self-Supervised Learning for Improved Highly-Accelerated MRI Reconstruction. ISBI 2024: 1-5 - [i24]Yasar Utku Alçalar, Mehmet Akçakaya:
Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse Problems. CoRR abs/2407.11288 (2024) - 2023
- [j19]Logan Dowdle
, Luca Vizioli, Steen Moeller, Mehmet Akçakaya, Cheryl Olman, Geoffrey Ghose, Essa Yacoub, Kâmil Ugurbil:
Evaluating increases in sensitivity from NORDIC for diverse fMRI acquisition strategies. NeuroImage 270: 119949 (2023) - [j18]Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya:
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging. IEEE Signal Process. Mag. 40(1): 98-114 (2023) - [c40]Merve Gülle, Ömer Burak Demirel, Logan Dowdle, Steen Moeller, Essa Yacoub, Kâmil Ugurbil, Mehmet Akçakaya:
Highly-Accelerated High-Resolution Multi-Echo fMRI Using Self-Supervised Physics-Driven Deep Learning Reconstruction. CAMSAP 2023: 196-200 - [c39]Ömer Burak Demirel, Chi Zhang, Burhaneddin Yaman, Merve Gülle, Chetan Shenoy, Tim Leiner, Peter Kellman, Mehmet Akçakaya:
High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI. EMBC 2023: 1-4 - [c38]Ömer Burak Demirel, Steen Moeller, Luca Vizioli, Burhaneddin Yaman, Logan Dowdle, Essa Yacoub, Kâmil Ugurbil, Mehmet Akçakaya:
High-Quality 0.5mm Isotropic fMRI: Random Matrix Theory Meets Physics-Driven Deep Learning. NER 2023: 1-6 - [i23]Hongyi Gu, Chi Zhang, Zidan Yu, Christoph Rettenmeier, V. Andrew Stenger, Mehmet Akçakaya:
Non-Cartesian Self-Supervised Physics-Driven Deep Learning Reconstruction for Highly-Accelerated Multi-Echo Spiral fMRI. CoRR abs/2312.05707 (2023) - 2022
- [j17]Chi Zhang, Steen Moeller, Omer Burak Demirel, Kâmil Ugurbil, Mehmet Akçakaya:
Residual RAKI: A hybrid linear and non-linear approach for scan-specific k-space deep learning. NeuroImage 256: 119248 (2022) - [j16]Mehmet Akçakaya, Burhaneddin Yaman, Hyungjin Chung, Jong Chul Ye:
Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancement: An overview from a signal processing perspective. IEEE Signal Process. Mag. 39(2): 28-44 (2022) - [j15]Syed Muhammad Anwar, Ismail Irmakci, Drew A. Torigian, Sachin Jambawalikar, Georgios Z. Papadakis, Can Akgun, Jutta Ellermann, Mehmet Akçakaya, Ulas Bagci:
Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI. J. Signal Process. Syst. 94(5): 497-510 (2022) - [c37]Ömer Burak Demirel, Burhaneddin Yaman, Steen Moeller, Sebastian Weingärtner, Mehmet Akçakaya:
Signal-Intensity Informed Multi-Coil MRI Encoding Operator for Improved Physics-Guided Deep Learning Reconstruction of Dynamic Contrast-Enhanced MRI. EMBC 2022: 1472-1476 - [c36]Chiara Coletti, Joao Tourais, Telly Ploem, Christal van de Steeg-Henzen, Mehmet Akçakaya, Sebastian Weingärtner:
Adiabatic spin-lock preparations enable robust in vivo cardiac $T_{1\rho}$-mapping at 3T. EMBC 2022: 1690-1693 - [c35]Joao Tourais, Omer Burak Demirel, Qian Tao, Iain Pierce, George D. Thornton, Thomas A. Treibel, Mehmet Akçakaya, Sebastian Weingärtner:
Myocardial Approximate Spin-lock Dispersion Mapping using a Simultaneous $T_{2}$ and $T_{RAFF2}$ Mapping at 3T MRI. EMBC 2022: 1694-1697 - [c34]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Mehmet Akçakaya:
Zero-Shot Self-Supervised Learning for MRI Reconstruction. ICLR 2022 - [c33]Chi Zhang, Davide Piccini, Ömer Burak Demirel, Gabriele Bonanno, Burhaneddin Yaman, Matthias Stuber, Steen Moeller, Mehmet Akçakaya:
Distributed Memory-Efficient Physics-Guided Deep Learning Reconstruction for Large-Scale 3d Non-Cartesian MRI. ISBI 2022: 1-5 - [i22]Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya:
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging. CoRR abs/2203.12215 (2022) - [i21]Hongyi Gu, Burhaneddin Yaman, Steen Moeller, Il Yong Chun, Mehmet Akçakaya:
Accelerated MRI With Deep Linear Convolutional Transform Learning. CoRR abs/2204.07923 (2022) - 2021
- [j14]Steen Moeller, Pramod Kumar Pisharady, Sudhir Ramanna, Christophe Lenglet, Xiaoping Wu, Logan Dowdle, Essa Yacoub, Kâmil Ugurbil, Mehmet Akçakaya:
NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing. NeuroImage 226: 117539 (2021) - [c32]Zilin Deng, Burhaneddin Yaman, Chi Zhang, Steen Moeller, Mehmet Akçakaya:
Efficient Training of 3D Unrolled Neural Networks for MRI Reconstruction Using Small Databases. ACSCC 2021: 886-889 - [c31]Ömer Burak Demirel, Burhaneddin Yaman, Logan Dowdle, Steen Moeller, Luca Vizioli, Essa Yacoub, John P. Strupp, Cheryl A. Olman, Kâmil Ugurbil, Mehmet Akçakaya:
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning. ACSCC 2021: 890-894 - [c30]Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya:
Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations. ACSCC 2021: 895-899 - [c29]Hongyi Gu, Burhaneddin Yaman, Kâmil Ugurbil, Steen Moeller, Mehmet Akçakaya:
Compressed Sensing MRI with ℓ1-Wavelet Reconstruction Revisited Using Modern Data Science Tools. EMBC 2021: 3596-3600 - [c28]Jaap Boon, Telly Ploem, Cole S. Simpson, Ingo Hermann, Mehmet Akçakaya, Edwin H. G. Oei, Amir Abbas Zadpoor, Nazli Tümer, Tom M. Piscaer, Joao Tourais, Sebastian Weingärtner:
Magnetic Resonance Imaging compatible Elastic Loading Mechanism (MELM): A minimal footprint device for MR imaging under load. EMBC 2021: 3721-3724 - [c27]Ömer Burak Demirel, Burhaneddin Yaman, Logan Dowdle, Steen Moeller, Luca Vizioli, Essa Yacoub, John P. Strupp, Cheryl A. Olman, Kâmil Ugurbil, Mehmet Akçakaya:
20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction. EMBC 2021: 3765-3769 - [c26]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Mehmet Akçakaya:
Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking. ICASSP 2021: 1150-1154 - [c25]Burhaneddin Yaman, Chetan Shenoy, Zilin Deng, Steen Moeller, Hossam El-Rewaidy, Reza Nezafat, Mehmet Akçakaya:
Self-Supervised Physics-Guided Deep Learning Reconstruction for High-Resolution 3D LGE CMR. ISBI 2021: 100-104 - [c24]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Jutta Ellermann, Kâmil Ugurbil, Mehmet Akçakaya:
Ground-Truth Free Multi-Mask Self-Supervised Physics-Guided Deep Learning in Highly Accelerated MRI. ISBI 2021: 1850-1854 - [i20]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Mehmet Akçakaya:
Scan-Specific MRI Reconstruction using Zero-Shot Physics-Guided Deep Learning. CoRR abs/2102.07737 (2021) - [i19]Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya:
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations. CoRR abs/2102.13066 (2021) - [i18]Ömer Burak Demirel, Burhaneddin Yaman, Logan Dowdle, Steen Moeller, Luca Vizioli, Essa Yacoub, John P. Strupp, Cheryl A. Olman, Kâmil Ugurbil, Mehmet Akçakaya:
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning. CoRR abs/2105.04532 (2021) - [i17]Ömer Burak Demirel, Burhaneddin Yaman, Logan Dowdle, Steen Moeller, Luca Vizioli, Essa Yacoub, John P. Strupp, Cheryl A. Olman, Kâmil Ugurbil, Mehmet Akçakaya:
20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction. CoRR abs/2105.05827 (2021) - [i16]Mehmet Akçakaya, Burhaneddin Yaman, Hyungjin Chung, Jong Chul Ye:
Unsupervised Deep Learning Methods for Biological Image Reconstruction. CoRR abs/2105.08040 (2021) - 2020
- [j13]Seyed Amir Hossein Hosseini, Burhaneddin Yaman, Steen Moeller, Mingyi Hong, Mehmet Akçakaya:
Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms. IEEE J. Sel. Top. Signal Process. 14(6): 1280-1291 (2020) - [j12]Ruoyun Ma, Mehmet Akçakaya, Steen Moeller, Edward J. Auerbach, Kâmil Ugurbil, Pierre-François van de Moortele:
A field-monitoring-based approach for correcting eddy-current-induced artifacts of up to the 2nd spatial order in human-connectome-project-style multiband diffusion MRI experiment at 7T: A pilot study. NeuroImage 216: 116861 (2020) - [j11]Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya:
Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. IEEE Signal Process. Mag. 37(1): 128-140 (2020) - [j10]Burhaneddin Yaman, Sebastian Weingärtner, Nikolaos Kargas, Nicholas D. Sidiropoulos, Mehmet Akçakaya:
Low-Rank Tensor Models for Improved Multidimensional MRI: Application to Dynamic Cardiac T1 Mapping. IEEE Trans. Computational Imaging 6: 194-207 (2020) - [j9]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mehmet Akçakaya:
Tensor Completion From Regular Sub-Nyquist Samples. IEEE Trans. Signal Process. 68: 1-16 (2020) - [c23]Seyed Amir Hossein Hosseini, Burhaneddin Yaman, Steen Moeller, Mehmet Akçakaya:
High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks. EMBC 2020: 1481-1484 - [c22]Seyed Amir Hossein Hosseini, Burhaneddin Yaman, Chi Zhang, Kâmil Ugurbil, Steen Moeller, Mehmet Akçakaya:
Scan-Specific Accelerated Mri Reconstruction Using Recurrent Neural Networks In A Regularized Self-Consistent Framework. ISBI Workshops 2020: 1-4 - [c21]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Jutta Ellermann, Kâmil Ugurbil, Mehmet Akçakaya:
Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data. ISBI 2020: 921-925 - [c20]Ömer Burak Demirel, Sebastian Weingärtner, Steen Moeller, Mehmet Akçakaya:
Improved Simultaneous Multi-Slice Imaging for Perfusion Cardiac MRI Using Outer Volume Suppression and Regularized Reconstruction. ISBI 2020: 1954-1957 - [c19]Patrick J. Bolan, Francesca Branzoli, Anna Luisa Di Stefano, Lucia Nichelli, Romain Valabrègue, Sara L. Saunders, Mehmet Akçakaya, Marc Sanson, Stéphane Lehéricy, Malgorzata Marjanska:
Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer. MICCAI (7) 2020: 730-739 - [i15]Arjun D. Desai, Francesco Calivá, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew A. Torigian, Jutta Ellermann, Mehmet Akçakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O'Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry Gold, Brian A. Hargreaves, Valentina Pedoia, Akshay S. Chaudhari:
The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset. CoRR abs/2004.14003 (2020) - [i14]Seyed Amir Hossein Hosseini, Burhaneddin Yaman, Steen Moeller, Mehmet Akçakaya:
High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks. CoRR abs/2005.05550 (2020) - [i13]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Mehmet Akçakaya:
Noise2Inpaint: Learning Referenceless Denoising by Inpainting Unrolling. CoRR abs/2006.09450 (2020) - [i12]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Jutta Ellermann, Kâmil Ugurbil, Mehmet Akçakaya:
Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI. CoRR abs/2008.06029 (2020) - [i11]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Mehmet Akçakaya:
Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking. CoRR abs/2010.13868 (2020) - [i10]Burhaneddin Yaman, Chetan Shenoy, Zilin Deng, Steen Moeller, Hossam El-Rewaidy, Reza Nezafat, Mehmet Akçakaya:
Self-Supervised Physics-Guided Deep Learning Reconstruction For High-Resolution 3D LGE CMR. CoRR abs/2011.09414 (2020)
2010 – 2019
- 2019
- [c18]Chi Zhang, Seyed Amir Hossein Hosseini, Steen Moeller, Sebastian Weingärtner, Kâmil Ugurbil, Mehmet Akçakaya:
Scan-Specific Residual Convolutional Neural Networks for Fast MRI Using Residual RAKI. ACSSC 2019: 1476-1480 - [c17]Sebastian Weingärtner, Ömer Burak Demirel, Chetan Shenoy, Lothar R. Schad, Jeanette Schulz-Menger, Mehmet Akçakaya:
Functional LGE Imaging: Cardiac Phase-Resolved Assessment of Focal Fibrosis. EMBC 2019: 3999-4003 - [c16]Ömer Burak Demirel, Sebastian Weingärtner, Steen Moeller, Mehmet Akçakaya:
Improved Regularized Reconstruction for Simultaneous Multi-Slice Cardiac MRI T1 Mapping. EUSIPCO 2019: 1-5 - [c15]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos, Mehmet Akçakaya, Xiao Fu:
Regular Sampling of Tensor Signals: Theory and Application to FMRI. ICASSP 2019: 2932-2936 - [c14]Seyed Amir Hossein Hosseini, Steen Moeller, Sebastian Weingärtner, Kâmil Ugurbil, Mehmet Akçakaya:
Accelerated Coronary Mri Using 3D Spirit-Raki With Sparsity Regularization. ISBI 2019: 1692-1695 - [c13]Sebastian Weingärtner, Xiaomo Chen, Mehmet Akçakaya, Tirin Moore:
Robust Online Spike Recovery for High-Density Electrode Recordings using Convolutional Compressed Sensing. NER 2019: 1015-1020 - [i9]Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya:
Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction. CoRR abs/1904.01112 (2019) - [i8]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Jutta Ellermann, Kâmil Ugurbil, Mehmet Akçakaya:
Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data. CoRR abs/1910.09116 (2019) - [i7]Seyed Amir Hossein Hosseini, Burhaneddin Yaman, Steen Moeller, Mingyi Hong, Mehmet Akçakaya:
Dense Recurrent Neural Networks for Inverse Problems: History-Cognizant Unrolling of Optimization Algorithms. CoRR abs/1912.07197 (2019) - [i6]Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Jutta Ellermann, Kâmil Ugurbil, Mehmet Akçakaya:
Self-Supervised Learning of Physics-Based Reconstruction Neural Networks without Fully-Sampled Reference Data. CoRR abs/1912.07669 (2019) - 2018
- [j8]Seyed Amir Hossein Hosseini, Abbas Sohrabpour, Mehmet Akçakaya, Bin He:
Electromagnetic Brain Source Imaging by Means of a Robust Minimum Variance Beamformer. IEEE Trans. Biomed. Eng. 65(10): 2365-2374 (2018) - [j7]Gang Wang, Liang Zhang, Georgios B. Giannakis, Mehmet Akçakaya, Jie Chen:
Sparse Phase Retrieval via Truncated Amplitude Flow. IEEE Trans. Signal Process. 66(2): 479-491 (2018) - [c12]Chi Zhang, Steen Moeller, Sebastian Weingärtner, Kâmil Ugurbil, Mehmet Akçakaya:
Accelerated Simultaneous Multi-Slice MRI using Subject-Specific Convolutional Neural Networks. ACSSC 2018: 1636-1640 - [c11]Chi Zhang, Sebastian Weingärtner, Steen Moeller, Kâmil Ugurbil, Mehmet Akçakaya:
Fast GPU Implementation of a Scan-Specific Deep Learning Reconstruction for Accelerated Magnetic Resonance Imaging. EIT 2018: 399-403 - [c10]Liang Zhang, Georgios Vasileios Karanikolas, Mehmet Akçakaya, Georgios B. Giannakis:
Fully Automatic Segmentation of the Right Ventricle Via Multi-Task Deep Neural Networks. ICASSP 2018: 6677-6681 - [c9]Mehmet Akçakaya, Steen Moeller, Sebastian Weingärtner, Kâmil Ugurbil:
Subject-Specific Convolutional Neural Networks for Accelerated Magnetic Resonance Imaging. IJCNN 2018: 1-6 - 2017
- [c8]Burhaneddin Yaman, Sebastian Weingärtner, Nikolaos Kargas, Nicholas D. Sidiropoulos, Mehmet Akçakaya:
Locally Low-Rank tensor regularization for high-resolution quantitative dynamic MRI. CAMSAP 2017: 1-5 - [c7]Steen Moeller, Sebastian Weingärtner, Mehmet Akçakaya:
Multi-scale locally low-rank noise reduction for high-resolution dynamic quantitative cardiac MRI. EMBC 2017: 1473-1476 - [c6]Gang Wang, Georgios B. Giannakis, Jie Chen, Mehmet Akçakaya:
SPARTA: Sparse phase retrieval via Truncated Amplitude flow. ICASSP 2017: 3974-3978 - 2016
- [i5]Gang Wang, Liang Zhang, Georgios B. Giannakis, Mehmet Akçakaya, Jie Chen:
Sparse Phase Retrieval via Truncated Amplitude Flow. CoRR abs/1611.07641 (2016) - 2015
- [j6]Mehmet Akçakaya, Vahid Tarokh:
Sparse Signal Recovery from a Mixture of Linear and Magnitude-Only Measurements. IEEE Signal Process. Lett. 22(9): 1220-1223 (2015) - 2013
- [c5]Mehmet Akçakaya, Vahid Tarokh:
Distortion-based achievability conditions for joint estimation of sparse signals and measurement parameters from undersampled acquisitions. ISIT 2013: 291-295 - [i4]Mehmet Akçakaya, Vahid Tarokh:
New Conditions for Sparse Phase Retrieval. CoRR abs/1310.1351 (2013) - 2011
- [j5]Mehmet Akçakaya, Seunghoon Nam, Peng Hu, Mehdi Hedjazi Moghari, Long H. Ngo, Vahid Tarokh, Warren J. Manning, Reza Nezafat:
Compressed Sensing With Wavelet Domain Dependencies for Coronary MRI: A Retrospective Study. IEEE Trans. Medical Imaging 30(5): 1090-1099 (2011) - [j4]Mehmet Akçakaya, Jinsoo Park, Vahid Tarokh:
A Coding Theory Approach to Noisy Compressive Sensing Using Low Density Frames. IEEE Trans. Signal Process. 59(11): 5369-5379 (2011) - 2010
- [j3]Mehmet Akçakaya, Vahid Tarokh:
Shannon-theoretic limits on noisy compressive sampling. IEEE Trans. Inf. Theory 56(1): 492-504 (2010) - [c4]Mehmet Akçakaya, Jinsoo Park, Vahid Tarokh:
Low density frames for compressive sensing. ICASSP 2010: 3642-3645
2000 – 2009
- 2009
- [i3]Mehmet Akçakaya, Jinsoo Park, Vahid Tarokh:
Compressive Sensing Using Low Density Frames. CoRR abs/0903.0650 (2009) - 2008
- [j2]Mehmet Akçakaya, Vahid Tarokh:
A Frame Construction and a Universal Distortion Bound for Sparse Representations. IEEE Trans. Signal Process. 56(6): 2443-2450 (2008) - [c3]Mehmet Akçakaya, Vahid Tarokh:
Noisy compressive sampling limits in linear and sublinear regimes. CISS 2008: 1-4 - 2007
- [j1]Mehmet Akçakaya, Vahid Tarokh:
Performance of Sparse Representation Algorithms Using Randomly Generated Frames. IEEE Signal Process. Lett. 14(11): 777-780 (2007) - [c2]Mehmet Akçakaya, Vahid Tarokh:
Performance Study of Various Sparse Representation Methods Using Redundant Frames. CISS 2007: 726-729 - [c1]Mehmet Akçakaya, Vahid Tarokh:
On Sparsity, Redundancy and Quality of Frame Representations. ISIT 2007: 951-955 - [i2]Mehmet Akçakaya, Vahid Tarokh:
Shannon Theoretic Limits on Noisy Compressive Sampling. CoRR abs/0711.0366 (2007) - [i1]Mehmet Akçakaya, Vahid Tarokh:
Performance Bounds on Sparse Representations Using Redundant Frames. CoRR abs/cs/0703045 (2007)
Coauthor Index
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