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ICASSP 2018

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The 2019 conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world. Visit website.

EXPLOITING EXPLICIT MEMORY INCLUSION FOR ARTIFICIAL BANDWIDTH EXTENSION


Artificial bandwidth extension (ABE) algorithms have been developed to improve speech quality when wideband devices are used in conjunction with narrowband devices or infrastructure. While past work points to the benefit of using contextual information or memory for ABE, an understanding of the relative benefit of explicit memory inclusion, rather than just dynamic information, calls for a comparative, quantitative analysis. The need for practical ABE solutions calls further for the inclusion of memory without significant increases to latency or computational complexity.

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Authors:
Massimiliano Todisco, Nicholas Evans
Submitted On:
12 April 2018 - 11:35am
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ICASSP2018_ABE_memory.pdf

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[1] Massimiliano Todisco, Nicholas Evans, "EXPLOITING EXPLICIT MEMORY INCLUSION FOR ARTIFICIAL BANDWIDTH EXTENSION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2397. Accessed: Jul. 19, 2019.
@article{2397-18,
url = {http://sigport.org/2397},
author = {Massimiliano Todisco; Nicholas Evans },
publisher = {IEEE SigPort},
title = {EXPLOITING EXPLICIT MEMORY INCLUSION FOR ARTIFICIAL BANDWIDTH EXTENSION},
year = {2018} }
TY - EJOUR
T1 - EXPLOITING EXPLICIT MEMORY INCLUSION FOR ARTIFICIAL BANDWIDTH EXTENSION
AU - Massimiliano Todisco; Nicholas Evans
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2397
ER -
Massimiliano Todisco, Nicholas Evans. (2018). EXPLOITING EXPLICIT MEMORY INCLUSION FOR ARTIFICIAL BANDWIDTH EXTENSION. IEEE SigPort. http://sigport.org/2397
Massimiliano Todisco, Nicholas Evans, 2018. EXPLOITING EXPLICIT MEMORY INCLUSION FOR ARTIFICIAL BANDWIDTH EXTENSION. Available at: http://sigport.org/2397.
Massimiliano Todisco, Nicholas Evans. (2018). "EXPLOITING EXPLICIT MEMORY INCLUSION FOR ARTIFICIAL BANDWIDTH EXTENSION." Web.
1. Massimiliano Todisco, Nicholas Evans. EXPLOITING EXPLICIT MEMORY INCLUSION FOR ARTIFICIAL BANDWIDTH EXTENSION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2397

EFFICACY OF MULTIUSER MASSIVE MISO WIRELESS ENERGY TRANSFER UNDER IQ IMBALANCE AND CHANNEL ESTIMATION ERRORS OVER RICIAN FADING


We investigate the practical realization of energy beamforming gains in the downlink wireless power transfer from a massive antenna radio frequency (RF) source to multiple single antenna energy harvesting (EH) users. Assuming channel reciprocity for the uplink and downlink channels undergoing Rician fading, we first obtain the least-squares and linear-minimum-mean-square-error channel estimates using the energy-constrained pilot signal transmission from EH users.

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Authors:
Deepak Mishra, Hakan Johansson
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12 April 2018 - 11:35am
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Poster for ICASSP18 presentation

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[1] Deepak Mishra, Hakan Johansson, "EFFICACY OF MULTIUSER MASSIVE MISO WIRELESS ENERGY TRANSFER UNDER IQ IMBALANCE AND CHANNEL ESTIMATION ERRORS OVER RICIAN FADING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2396. Accessed: Jul. 19, 2019.
@article{2396-18,
url = {http://sigport.org/2396},
author = {Deepak Mishra; Hakan Johansson },
publisher = {IEEE SigPort},
title = {EFFICACY OF MULTIUSER MASSIVE MISO WIRELESS ENERGY TRANSFER UNDER IQ IMBALANCE AND CHANNEL ESTIMATION ERRORS OVER RICIAN FADING},
year = {2018} }
TY - EJOUR
T1 - EFFICACY OF MULTIUSER MASSIVE MISO WIRELESS ENERGY TRANSFER UNDER IQ IMBALANCE AND CHANNEL ESTIMATION ERRORS OVER RICIAN FADING
AU - Deepak Mishra; Hakan Johansson
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2396
ER -
Deepak Mishra, Hakan Johansson. (2018). EFFICACY OF MULTIUSER MASSIVE MISO WIRELESS ENERGY TRANSFER UNDER IQ IMBALANCE AND CHANNEL ESTIMATION ERRORS OVER RICIAN FADING. IEEE SigPort. http://sigport.org/2396
Deepak Mishra, Hakan Johansson, 2018. EFFICACY OF MULTIUSER MASSIVE MISO WIRELESS ENERGY TRANSFER UNDER IQ IMBALANCE AND CHANNEL ESTIMATION ERRORS OVER RICIAN FADING. Available at: http://sigport.org/2396.
Deepak Mishra, Hakan Johansson. (2018). "EFFICACY OF MULTIUSER MASSIVE MISO WIRELESS ENERGY TRANSFER UNDER IQ IMBALANCE AND CHANNEL ESTIMATION ERRORS OVER RICIAN FADING." Web.
1. Deepak Mishra, Hakan Johansson. EFFICACY OF MULTIUSER MASSIVE MISO WIRELESS ENERGY TRANSFER UNDER IQ IMBALANCE AND CHANNEL ESTIMATION ERRORS OVER RICIAN FADING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2396

Low-Overhead Receiver-side Channel Tracking for mmWave MIMO


Millimeter wave (mmWave) multiple-input multiple-output (MIMO) transceivers employ narrow beams to obtain a large array-gain, rendering them sensitive to changes in the angles of arrival and departure of the paths. Since the singular vectors that span the channel subspace are used to design the precoder and combiner, we propose a method to track the receiver-side channel subspace during data transmission using a separate radio frequency (RF) chain dedicated for channel tracking.

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24 April 2018 - 6:43pm
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[1] , "Low-Overhead Receiver-side Channel Tracking for mmWave MIMO", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2395. Accessed: Jul. 19, 2019.
@article{2395-18,
url = {http://sigport.org/2395},
author = { },
publisher = {IEEE SigPort},
title = {Low-Overhead Receiver-side Channel Tracking for mmWave MIMO},
year = {2018} }
TY - EJOUR
T1 - Low-Overhead Receiver-side Channel Tracking for mmWave MIMO
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2395
ER -
. (2018). Low-Overhead Receiver-side Channel Tracking for mmWave MIMO. IEEE SigPort. http://sigport.org/2395
, 2018. Low-Overhead Receiver-side Channel Tracking for mmWave MIMO. Available at: http://sigport.org/2395.
. (2018). "Low-Overhead Receiver-side Channel Tracking for mmWave MIMO." Web.
1. . Low-Overhead Receiver-side Channel Tracking for mmWave MIMO [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2395

Deep Geometric Matrix Completion

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Authors:
Federico Monti, Michael M. Bronstein, Xavier Bresson
Submitted On:
12 April 2018 - 5:42pm
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[1] Federico Monti, Michael M. Bronstein, Xavier Bresson, "Deep Geometric Matrix Completion", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2394. Accessed: Jul. 19, 2019.
@article{2394-18,
url = {http://sigport.org/2394},
author = {Federico Monti; Michael M. Bronstein; Xavier Bresson },
publisher = {IEEE SigPort},
title = {Deep Geometric Matrix Completion},
year = {2018} }
TY - EJOUR
T1 - Deep Geometric Matrix Completion
AU - Federico Monti; Michael M. Bronstein; Xavier Bresson
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2394
ER -
Federico Monti, Michael M. Bronstein, Xavier Bresson. (2018). Deep Geometric Matrix Completion. IEEE SigPort. http://sigport.org/2394
Federico Monti, Michael M. Bronstein, Xavier Bresson, 2018. Deep Geometric Matrix Completion. Available at: http://sigport.org/2394.
Federico Monti, Michael M. Bronstein, Xavier Bresson. (2018). "Deep Geometric Matrix Completion." Web.
1. Federico Monti, Michael M. Bronstein, Xavier Bresson. Deep Geometric Matrix Completion [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2394

ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY


Random sample consensus (RANSAC) is a popular paradigm for parameter estimation with outlier detection, which plays an essential role in 3D robot vision, especially for LiDAR odometry. The success of RANSAC strongly depends on the probability of selecting a subset of pure inliers, which sets barriers to robust and fast parameter estimation. Although significant efforts have been made to improve RANSAC in various scenarios, its strong dependency on inlier selection is still a problem.

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Authors:
Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin
Submitted On:
12 April 2018 - 11:26am
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[1] Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin, "ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2393. Accessed: Jul. 19, 2019.
@article{2393-18,
url = {http://sigport.org/2393},
author = {Hui Cheng; Yongheng Hu; Chongyu Chen; and Liang Lin },
publisher = {IEEE SigPort},
title = {ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY},
year = {2018} }
TY - EJOUR
T1 - ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY
AU - Hui Cheng; Yongheng Hu; Chongyu Chen; and Liang Lin
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2393
ER -
Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin. (2018). ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY. IEEE SigPort. http://sigport.org/2393
Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin, 2018. ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY. Available at: http://sigport.org/2393.
Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin. (2018). "ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY." Web.
1. Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin. ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2393

3D IMAGE RECONSTRUCTION FROM MULTI-FOCUS MICROSCOPE: AXIAL SUPER-RESOLUTION AND MULTIPLE-FRAME PROCESSING

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Authors:
Pablo Ruiz, Xiang Huang, Kuan He, Nicola J. Ferrier, Mark Hereld, Alan Selewa, Matthew Daddysman, Norbert Scherer, Oliver Cossairt, Aggelos K. Katsaggelos
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12 April 2018 - 4:33pm
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[1] Pablo Ruiz, Xiang Huang, Kuan He, Nicola J. Ferrier, Mark Hereld, Alan Selewa, Matthew Daddysman, Norbert Scherer, Oliver Cossairt, Aggelos K. Katsaggelos, "3D IMAGE RECONSTRUCTION FROM MULTI-FOCUS MICROSCOPE: AXIAL SUPER-RESOLUTION AND MULTIPLE-FRAME PROCESSING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2392. Accessed: Jul. 19, 2019.
@article{2392-18,
url = {http://sigport.org/2392},
author = {Pablo Ruiz; Xiang Huang; Kuan He; Nicola J. Ferrier; Mark Hereld; Alan Selewa; Matthew Daddysman; Norbert Scherer; Oliver Cossairt; Aggelos K. Katsaggelos },
publisher = {IEEE SigPort},
title = {3D IMAGE RECONSTRUCTION FROM MULTI-FOCUS MICROSCOPE: AXIAL SUPER-RESOLUTION AND MULTIPLE-FRAME PROCESSING},
year = {2018} }
TY - EJOUR
T1 - 3D IMAGE RECONSTRUCTION FROM MULTI-FOCUS MICROSCOPE: AXIAL SUPER-RESOLUTION AND MULTIPLE-FRAME PROCESSING
AU - Pablo Ruiz; Xiang Huang; Kuan He; Nicola J. Ferrier; Mark Hereld; Alan Selewa; Matthew Daddysman; Norbert Scherer; Oliver Cossairt; Aggelos K. Katsaggelos
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2392
ER -
Pablo Ruiz, Xiang Huang, Kuan He, Nicola J. Ferrier, Mark Hereld, Alan Selewa, Matthew Daddysman, Norbert Scherer, Oliver Cossairt, Aggelos K. Katsaggelos. (2018). 3D IMAGE RECONSTRUCTION FROM MULTI-FOCUS MICROSCOPE: AXIAL SUPER-RESOLUTION AND MULTIPLE-FRAME PROCESSING. IEEE SigPort. http://sigport.org/2392
Pablo Ruiz, Xiang Huang, Kuan He, Nicola J. Ferrier, Mark Hereld, Alan Selewa, Matthew Daddysman, Norbert Scherer, Oliver Cossairt, Aggelos K. Katsaggelos, 2018. 3D IMAGE RECONSTRUCTION FROM MULTI-FOCUS MICROSCOPE: AXIAL SUPER-RESOLUTION AND MULTIPLE-FRAME PROCESSING. Available at: http://sigport.org/2392.
Pablo Ruiz, Xiang Huang, Kuan He, Nicola J. Ferrier, Mark Hereld, Alan Selewa, Matthew Daddysman, Norbert Scherer, Oliver Cossairt, Aggelos K. Katsaggelos. (2018). "3D IMAGE RECONSTRUCTION FROM MULTI-FOCUS MICROSCOPE: AXIAL SUPER-RESOLUTION AND MULTIPLE-FRAME PROCESSING." Web.
1. Pablo Ruiz, Xiang Huang, Kuan He, Nicola J. Ferrier, Mark Hereld, Alan Selewa, Matthew Daddysman, Norbert Scherer, Oliver Cossairt, Aggelos K. Katsaggelos. 3D IMAGE RECONSTRUCTION FROM MULTI-FOCUS MICROSCOPE: AXIAL SUPER-RESOLUTION AND MULTIPLE-FRAME PROCESSING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2392

FAST AND ADAPTIVE BLIND AUDIO SOURCE SEPARATION USING RECURSIVE LEVENBERG-MARQUARDT SYNCHROSQUEEZING


This paper revisits the Degenerate Unmixing Estimation Technique (DUET) for blind audio separation of an arbitrary
number of sources given two mixtures through a recursively computed and adaptive time-frequency representation.
Recently, synchrosqueezing was introduced as a promising signal disentangling method which allows to compute reversible
and sharpen time-frequency representations. Thus, it can be used to reduce overlaps between the sources in the

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Authors:
Dominique Fourer, Geoffroy Peeters
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12 April 2018 - 11:22am
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[1] Dominique Fourer, Geoffroy Peeters, "FAST AND ADAPTIVE BLIND AUDIO SOURCE SEPARATION USING RECURSIVE LEVENBERG-MARQUARDT SYNCHROSQUEEZING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2391. Accessed: Jul. 19, 2019.
@article{2391-18,
url = {http://sigport.org/2391},
author = {Dominique Fourer; Geoffroy Peeters },
publisher = {IEEE SigPort},
title = {FAST AND ADAPTIVE BLIND AUDIO SOURCE SEPARATION USING RECURSIVE LEVENBERG-MARQUARDT SYNCHROSQUEEZING},
year = {2018} }
TY - EJOUR
T1 - FAST AND ADAPTIVE BLIND AUDIO SOURCE SEPARATION USING RECURSIVE LEVENBERG-MARQUARDT SYNCHROSQUEEZING
AU - Dominique Fourer; Geoffroy Peeters
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2391
ER -
Dominique Fourer, Geoffroy Peeters. (2018). FAST AND ADAPTIVE BLIND AUDIO SOURCE SEPARATION USING RECURSIVE LEVENBERG-MARQUARDT SYNCHROSQUEEZING. IEEE SigPort. http://sigport.org/2391
Dominique Fourer, Geoffroy Peeters, 2018. FAST AND ADAPTIVE BLIND AUDIO SOURCE SEPARATION USING RECURSIVE LEVENBERG-MARQUARDT SYNCHROSQUEEZING. Available at: http://sigport.org/2391.
Dominique Fourer, Geoffroy Peeters. (2018). "FAST AND ADAPTIVE BLIND AUDIO SOURCE SEPARATION USING RECURSIVE LEVENBERG-MARQUARDT SYNCHROSQUEEZING." Web.
1. Dominique Fourer, Geoffroy Peeters. FAST AND ADAPTIVE BLIND AUDIO SOURCE SEPARATION USING RECURSIVE LEVENBERG-MARQUARDT SYNCHROSQUEEZING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2391

ANALYSIS OF MULTILINGUAL BLSTM ACOUSTIC MODEL ON AND HIGH RESOURCE LANGUAGES


The paper provides an analysis of automatic speech recognition
systems (ASR) based on multilingual BLSTM, where we used multi-task
training with separate classification layer for each language. The
focus is on low resource languages, where only a limited
amount of transcribed speech is available. In such
scenario, we found it
essential to train the ASR systems in a multilingual fashion and we
report superior results
obtained with pre-trained multilingual BLSTM on this task.
The high resource languages are also

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12 April 2018 - 11:22am
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[1] , " ANALYSIS OF MULTILINGUAL BLSTM ACOUSTIC MODEL ON AND HIGH RESOURCE LANGUAGES", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2390. Accessed: Jul. 19, 2019.
@article{2390-18,
url = {http://sigport.org/2390},
author = { },
publisher = {IEEE SigPort},
title = { ANALYSIS OF MULTILINGUAL BLSTM ACOUSTIC MODEL ON AND HIGH RESOURCE LANGUAGES},
year = {2018} }
TY - EJOUR
T1 - ANALYSIS OF MULTILINGUAL BLSTM ACOUSTIC MODEL ON AND HIGH RESOURCE LANGUAGES
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2390
ER -
. (2018). ANALYSIS OF MULTILINGUAL BLSTM ACOUSTIC MODEL ON AND HIGH RESOURCE LANGUAGES. IEEE SigPort. http://sigport.org/2390
, 2018. ANALYSIS OF MULTILINGUAL BLSTM ACOUSTIC MODEL ON AND HIGH RESOURCE LANGUAGES. Available at: http://sigport.org/2390.
. (2018). " ANALYSIS OF MULTILINGUAL BLSTM ACOUSTIC MODEL ON AND HIGH RESOURCE LANGUAGES." Web.
1. . ANALYSIS OF MULTILINGUAL BLSTM ACOUSTIC MODEL ON AND HIGH RESOURCE LANGUAGES [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2390

PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING

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Authors:
Shuo Zheng, Marco Cagnazzo, Michel Kieffer
Submitted On:
12 April 2018 - 11:29am
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PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING

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[1] Shuo Zheng, Marco Cagnazzo, Michel Kieffer, "PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2387. Accessed: Jul. 19, 2019.
@article{2387-18,
url = {http://sigport.org/2387},
author = {Shuo Zheng; Marco Cagnazzo; Michel Kieffer },
publisher = {IEEE SigPort},
title = {PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING},
year = {2018} }
TY - EJOUR
T1 - PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING
AU - Shuo Zheng; Marco Cagnazzo; Michel Kieffer
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2387
ER -
Shuo Zheng, Marco Cagnazzo, Michel Kieffer. (2018). PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING. IEEE SigPort. http://sigport.org/2387
Shuo Zheng, Marco Cagnazzo, Michel Kieffer, 2018. PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING. Available at: http://sigport.org/2387.
Shuo Zheng, Marco Cagnazzo, Michel Kieffer. (2018). "PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING." Web.
1. Shuo Zheng, Marco Cagnazzo, Michel Kieffer. PRECODING MATRIX DESIGN IN LINEAR VIDEO CODING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2387

REMOVING RING ARTIFACTS IN CBCT IMAGES VIA GENERATIVE ADVERSARIAL NETWORK


Cone-beam computed tomography (CBCT) images often have some ring artifacts because of the inconsistent response of detector pixels. Removing ring artifacts in CBCT images without impairing the image quality is critical for the application of CBCT. In this paper, we explore this issue as an “adversarial problem” and propose a novel method to eliminate ring artifacts from CBCT images by using an imageto-image network based on Generative Adversarial Network (GAN).

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Authors:
Shuyang Zhao,Jianwu Li, Qirun Huo
Submitted On:
12 April 2018 - 11:27am
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ICASSP2018-2121-Poster

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[1] Shuyang Zhao,Jianwu Li, Qirun Huo, "REMOVING RING ARTIFACTS IN CBCT IMAGES VIA GENERATIVE ADVERSARIAL NETWORK", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2386. Accessed: Jul. 19, 2019.
@article{2386-18,
url = {http://sigport.org/2386},
author = {Shuyang Zhao;Jianwu Li; Qirun Huo },
publisher = {IEEE SigPort},
title = {REMOVING RING ARTIFACTS IN CBCT IMAGES VIA GENERATIVE ADVERSARIAL NETWORK},
year = {2018} }
TY - EJOUR
T1 - REMOVING RING ARTIFACTS IN CBCT IMAGES VIA GENERATIVE ADVERSARIAL NETWORK
AU - Shuyang Zhao;Jianwu Li; Qirun Huo
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2386
ER -
Shuyang Zhao,Jianwu Li, Qirun Huo. (2018). REMOVING RING ARTIFACTS IN CBCT IMAGES VIA GENERATIVE ADVERSARIAL NETWORK. IEEE SigPort. http://sigport.org/2386
Shuyang Zhao,Jianwu Li, Qirun Huo, 2018. REMOVING RING ARTIFACTS IN CBCT IMAGES VIA GENERATIVE ADVERSARIAL NETWORK. Available at: http://sigport.org/2386.
Shuyang Zhao,Jianwu Li, Qirun Huo. (2018). "REMOVING RING ARTIFACTS IN CBCT IMAGES VIA GENERATIVE ADVERSARIAL NETWORK." Web.
1. Shuyang Zhao,Jianwu Li, Qirun Huo. REMOVING RING ARTIFACTS IN CBCT IMAGES VIA GENERATIVE ADVERSARIAL NETWORK [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2386

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