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AngioNet: a convolutional neural network for vessel segmentation in X-ray angiography

Scientific reports, 2021-09, Vol.11 (1), p.18066-18066, Article 18066

2021

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A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images

Scientific reports, 2023-10, Vol.13 (1), p.17603-17603, Article 17603

2023

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Random matrix theory enabled performance analysis and algorithms for underwater signal processing

The Journal of the Acoustical Society of America, 2015-09, Vol.138 (3_Supplement), p.1840-1840

Nadakuditi, Raj R.

2015

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Random matrix theory and performance prediction of subspace methods

The Journal of the Acoustical Society of America, 2012-09, Vol.132 (3_Supplement), p.2006-2006

Nadakuditi, Raj R.

2012

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On the costs and benefits of stochasticity in stream processing

Design Automation Conference, 2010, p.320-325

2010

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A channel subspace filtering approach to adaptive equalization of realistic acoustic channels

The Journal of the Acoustical Society of America, 2001-05, Vol.109 (5_Supplement), p.2476-2476

2001

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OptShrink: An Algorithm for Improved Low-Rank Signal Matrix Denoising by Optimal, Data-Driven Singular Value Shrinkage

IEEE transactions on information theory, 2014-05, Vol.60 (5), p.3002-3018

Nadakuditi, Raj Rao

2014

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Sample Eigenvalue Based Detection of High-Dimensional Signals in White Noise Using Relatively Few Samples

IEEE transactions on signal processing, 2008-07, Vol.56 (7), p.2625-2638

2008

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The Performance of a Matched Subspace Detector That Uses Subspaces Estimated From Finite, Noisy, Training Data

IEEE transactions on signal processing, 2013-04, Vol.61 (8), p.1972-1985

2013

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Exploiting random matrix theory to improve noisy low-rank matrix approximation

2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2011, p.769-773

Nadakuditi, R. R.

2011

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A channel subspace post-filtering approach to adaptive least-squares estimation

IEEE transactions on signal processing, 2004-07, Vol.52 (7), p.1901-1914

2004

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Improving and characterizing the performance of stochastic matched subspace detectors when using noisy estimated subspaces

2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2011, p.1893-1897

2011

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The breakdown point of signal subspace estimation

2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, 2010, p.177-180

2010

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On hard limits of eigen-analysis based planted clique detection

2012 IEEE Statistical Signal Processing Workshop (SSP), 2012, p.129-132

Nadakuditi, R. R.

2012

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Fundamental finite-sample limit of canonical correlation analysis based detection of correlated high-dimensional signals in white noise

2011 IEEE Statistical Signal Processing Workshop (SSP), 2011, p.397-400

Nadakuditi, R. R.

2011

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The performance of music-based DOA in white noise with missing data

2012 IEEE Statistical Signal Processing Workshop (SSP), 2012, p.800-803

2012

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A channel subspace filtering approach to adaptive equalization of highly dynamic realistic channels

Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256), 2001, Vol.2, p.1616-1623 vol.2

2001

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The performance of deterministic matched subspace detectors when using subspaces estimated from noisy, missing data

2012 IEEE Statistical Signal Processing Workshop (SSP), 2012, p.397-400

2012

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An iterative, backscatter-analysis based algorithm for increasing transmission through a highly-backscattering random medium

2012 IEEE Statistical Signal Processing Workshop (SSP), 2012, p.97-100

2012

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AngioNet: a convolutional neural network for vessel segmentation in X-ray angiography

A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images

Random matrix theory enabled performance analysis and algorithms for underwater signal processing

Random matrix theory and performance prediction of subspace methods

On the costs and benefits of stochasticity in stream processing

A channel subspace filtering approach to adaptive equalization of realistic acoustic channels

OptShrink: An Algorithm for Improved Low-Rank Signal Matrix Denoising by Optimal, Data-Driven Singular Value Shrinkage

Sample Eigenvalue Based Detection of High-Dimensional Signals in White Noise Using Relatively Few Samples

The Performance of a Matched Subspace Detector That Uses Subspaces Estimated From Finite, Noisy, Training Data

Exploiting random matrix theory to improve noisy low-rank matrix approximation

A channel subspace post-filtering approach to adaptive least-squares estimation

Improving and characterizing the performance of stochastic matched subspace detectors when using noisy estimated subspaces

The breakdown point of signal subspace estimation

On hard limits of eigen-analysis based planted clique detection

Fundamental finite-sample limit of canonical correlation analysis based detection of correlated high-dimensional signals in white noise

The performance of music-based DOA in white noise with missing data

A channel subspace filtering approach to adaptive equalization of highly dynamic realistic channels

The performance of deterministic matched subspace detectors when using subspaces estimated from noisy, missing data

An iterative, backscatter-analysis based algorithm for increasing transmission through a highly-backscattering random medium

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