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ICASSP 2020

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The ICASSP 2020 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.

Multi-step Online Unsupervised Domain Adaptation


In this paper, we address the Online Unsupervised Domain Adaptation (OUDA) problem, where the target data are unlabelled and arriving sequentially. The traditional methods on the OUDA problem mainly focus on transforming each arriving target data to the source domain, and they do not sufficiently consider the temporal coherency and accumulative statistics among the arriving target data. We propose a multi-step framework for the OUDA problem, which institutes a novel method to compute the mean-target subspace inspired by the geometrical interpretation on the Euclidean space.

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Authors:
J. H. Moon, Debasmit Das, and C. S. George Lee
Submitted On:
14 May 2020 - 11:58pm
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ICASSP2020_Jihoon Moon_final_4.pdf

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[1] J. H. Moon, Debasmit Das, and C. S. George Lee, "Multi-step Online Unsupervised Domain Adaptation", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5331. Accessed: Jul. 06, 2020.
@article{5331-20,
url = {http://sigport.org/5331},
author = {J. H. Moon; Debasmit Das; and C. S. George Lee },
publisher = {IEEE SigPort},
title = {Multi-step Online Unsupervised Domain Adaptation},
year = {2020} }
TY - EJOUR
T1 - Multi-step Online Unsupervised Domain Adaptation
AU - J. H. Moon; Debasmit Das; and C. S. George Lee
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5331
ER -
J. H. Moon, Debasmit Das, and C. S. George Lee. (2020). Multi-step Online Unsupervised Domain Adaptation. IEEE SigPort. http://sigport.org/5331
J. H. Moon, Debasmit Das, and C. S. George Lee, 2020. Multi-step Online Unsupervised Domain Adaptation. Available at: http://sigport.org/5331.
J. H. Moon, Debasmit Das, and C. S. George Lee. (2020). "Multi-step Online Unsupervised Domain Adaptation." Web.
1. J. H. Moon, Debasmit Das, and C. S. George Lee. Multi-step Online Unsupervised Domain Adaptation [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5331

HIGH-ACCURACY CLASSIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER WITH L2,1-NORM LINEAR DISCRIMINANT ANALYSIS

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Authors:
Yibin Tang, Xufei Li, Ying Chen, Yuan Zhong, Aimin Jiang, Xiaofeng Liu
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14 May 2020 - 10:55pm
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High-accuracy Classification of Attention Deficit Hyperactivity Disorder with L2,1-norm Linear Discriminant Analysis

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[1] Yibin Tang, Xufei Li, Ying Chen, Yuan Zhong, Aimin Jiang, Xiaofeng Liu, "HIGH-ACCURACY CLASSIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER WITH L2,1-NORM LINEAR DISCRIMINANT ANALYSIS", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5330. Accessed: Jul. 06, 2020.
@article{5330-20,
url = {http://sigport.org/5330},
author = {Yibin Tang; Xufei Li; Ying Chen; Yuan Zhong; Aimin Jiang; Xiaofeng Liu },
publisher = {IEEE SigPort},
title = {HIGH-ACCURACY CLASSIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER WITH L2,1-NORM LINEAR DISCRIMINANT ANALYSIS},
year = {2020} }
TY - EJOUR
T1 - HIGH-ACCURACY CLASSIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER WITH L2,1-NORM LINEAR DISCRIMINANT ANALYSIS
AU - Yibin Tang; Xufei Li; Ying Chen; Yuan Zhong; Aimin Jiang; Xiaofeng Liu
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5330
ER -
Yibin Tang, Xufei Li, Ying Chen, Yuan Zhong, Aimin Jiang, Xiaofeng Liu. (2020). HIGH-ACCURACY CLASSIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER WITH L2,1-NORM LINEAR DISCRIMINANT ANALYSIS. IEEE SigPort. http://sigport.org/5330
Yibin Tang, Xufei Li, Ying Chen, Yuan Zhong, Aimin Jiang, Xiaofeng Liu, 2020. HIGH-ACCURACY CLASSIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER WITH L2,1-NORM LINEAR DISCRIMINANT ANALYSIS. Available at: http://sigport.org/5330.
Yibin Tang, Xufei Li, Ying Chen, Yuan Zhong, Aimin Jiang, Xiaofeng Liu. (2020). "HIGH-ACCURACY CLASSIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER WITH L2,1-NORM LINEAR DISCRIMINANT ANALYSIS." Web.
1. Yibin Tang, Xufei Li, Ying Chen, Yuan Zhong, Aimin Jiang, Xiaofeng Liu. HIGH-ACCURACY CLASSIFICATION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER WITH L2,1-NORM LINEAR DISCRIMINANT ANALYSIS [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5330

Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance


In low light condition, color (RGB) images captured by camera contain much noise and loss of details and color. However, near infrared (NIR) images are robust to noise and have clear textures without color. In this paper, we propose multi-spectral fusion of RGB and NIR images using weighted least squares (WLS) and alternating guidance. Low light RGB images provide coarse image structure and color, while NIR images offer clear textures in a short distance. Since they are complementary, we adopt alternating guidance for fusion of RGB and NIR images based on WLS.

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Authors:
Kailong Zhou,Cheolkon Jung
Submitted On:
14 May 2020 - 10:07pm
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ICASSP2020_Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance.pdf

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[1] Kailong Zhou,Cheolkon Jung, "Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5329. Accessed: Jul. 06, 2020.
@article{5329-20,
url = {http://sigport.org/5329},
author = {Kailong Zhou,Cheolkon Jung },
publisher = {IEEE SigPort},
title = {Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance},
year = {2020} }
TY - EJOUR
T1 - Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance
AU - Kailong Zhou,Cheolkon Jung
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5329
ER -
Kailong Zhou,Cheolkon Jung. (2020). Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance. IEEE SigPort. http://sigport.org/5329
Kailong Zhou,Cheolkon Jung, 2020. Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance. Available at: http://sigport.org/5329.
Kailong Zhou,Cheolkon Jung. (2020). "Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance." Web.
1. Kailong Zhou,Cheolkon Jung. Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Alternating Guidance [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5329

Joint Sparse Recovery using Deep Unfolding With Application to Massive Random Access

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14 May 2020 - 9:29pm
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SrikrishnaBhashyamICASSP2020.pdf

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[1] , "Joint Sparse Recovery using Deep Unfolding With Application to Massive Random Access", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5328. Accessed: Jul. 06, 2020.
@article{5328-20,
url = {http://sigport.org/5328},
author = { },
publisher = {IEEE SigPort},
title = {Joint Sparse Recovery using Deep Unfolding With Application to Massive Random Access},
year = {2020} }
TY - EJOUR
T1 - Joint Sparse Recovery using Deep Unfolding With Application to Massive Random Access
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5328
ER -
. (2020). Joint Sparse Recovery using Deep Unfolding With Application to Massive Random Access. IEEE SigPort. http://sigport.org/5328
, 2020. Joint Sparse Recovery using Deep Unfolding With Application to Massive Random Access. Available at: http://sigport.org/5328.
. (2020). "Joint Sparse Recovery using Deep Unfolding With Application to Massive Random Access." Web.
1. . Joint Sparse Recovery using Deep Unfolding With Application to Massive Random Access [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5328

Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters


Altitude estimation is important for successful control and navigation of unmanned aerial vehicles (UAVs). UAVs do not have indoor access to GPS signals and can only use on-board sensors for reliable estimation of altitude. Unfortunately, most existing navigation schemes are not robust to the presence of abnormal obstructions above and below the UAV.

Paper Details

Authors:
Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo
Submitted On:
14 May 2020 - 8:35pm
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ICASSP 2020.pdf

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[1] Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo, "Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5327. Accessed: Jul. 06, 2020.
@article{5327-20,
url = {http://sigport.org/5327},
author = {Liu Yang; Hechuan Wang; Yousef El-Laham; José Fonte; David Pérez; Mónica F. Bugallo },
publisher = {IEEE SigPort},
title = {Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters},
year = {2020} }
TY - EJOUR
T1 - Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters
AU - Liu Yang; Hechuan Wang; Yousef El-Laham; José Fonte; David Pérez; Mónica F. Bugallo
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5327
ER -
Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo. (2020). Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters. IEEE SigPort. http://sigport.org/5327
Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo, 2020. Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters. Available at: http://sigport.org/5327.
Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo. (2020). "Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters." Web.
1. Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo. Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5327

Learning Product Graphs from Multidomain Signals


In this paper, we focus on learning the underlying product graph structure from multidomain training data. We assume that the product graph is formed from a Cartesian graph product of two smaller factor graphs. We then pose the product graph learning problem as the factor graph Laplacian matrix estimation problem. To estimate the factor graph Laplacian matrices, we assume that the data is smooth with respect to the underlying product graph.

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Authors:
Sai Kiran Kadambari, Sundeep Prabhakar Chepuri
Submitted On:
14 May 2020 - 7:38pm
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ICASSP20_Slides_sai.pdf

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[1] Sai Kiran Kadambari, Sundeep Prabhakar Chepuri, "Learning Product Graphs from Multidomain Signals", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5325. Accessed: Jul. 06, 2020.
@article{5325-20,
url = {http://sigport.org/5325},
author = {Sai Kiran Kadambari; Sundeep Prabhakar Chepuri },
publisher = {IEEE SigPort},
title = {Learning Product Graphs from Multidomain Signals},
year = {2020} }
TY - EJOUR
T1 - Learning Product Graphs from Multidomain Signals
AU - Sai Kiran Kadambari; Sundeep Prabhakar Chepuri
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5325
ER -
Sai Kiran Kadambari, Sundeep Prabhakar Chepuri. (2020). Learning Product Graphs from Multidomain Signals. IEEE SigPort. http://sigport.org/5325
Sai Kiran Kadambari, Sundeep Prabhakar Chepuri, 2020. Learning Product Graphs from Multidomain Signals. Available at: http://sigport.org/5325.
Sai Kiran Kadambari, Sundeep Prabhakar Chepuri. (2020). "Learning Product Graphs from Multidomain Signals." Web.
1. Sai Kiran Kadambari, Sundeep Prabhakar Chepuri. Learning Product Graphs from Multidomain Signals [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5325

Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis


Despite the ability to produce human-level speech for in-domain text, attention-based end-to-end text-to-speech (TTS) systems suffer from text alignment failures that increase in frequency for out-of-domain text. We show that these failures can be addressed using simple location-relative attention mechanisms that do away with content-based query/key comparisons. We compare two families of attention mechanisms: location-relative GMM-based mechanisms and additive energy-based mechanisms.

Paper Details

Authors:
Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad, Daisy Stanton, David Kao, Matt Shannon, Tom Bagby
Submitted On:
14 May 2020 - 6:30pm
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Location-Relative Attention (slides).pdf

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[1] Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad, Daisy Stanton, David Kao, Matt Shannon, Tom Bagby, "Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5324. Accessed: Jul. 06, 2020.
@article{5324-20,
url = {http://sigport.org/5324},
author = {Eric Battenberg; RJ Skerry-Ryan; Soroosh Mariooryad; Daisy Stanton; David Kao; Matt Shannon; Tom Bagby },
publisher = {IEEE SigPort},
title = {Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis},
year = {2020} }
TY - EJOUR
T1 - Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis
AU - Eric Battenberg; RJ Skerry-Ryan; Soroosh Mariooryad; Daisy Stanton; David Kao; Matt Shannon; Tom Bagby
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5324
ER -
Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad, Daisy Stanton, David Kao, Matt Shannon, Tom Bagby. (2020). Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis. IEEE SigPort. http://sigport.org/5324
Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad, Daisy Stanton, David Kao, Matt Shannon, Tom Bagby, 2020. Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis. Available at: http://sigport.org/5324.
Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad, Daisy Stanton, David Kao, Matt Shannon, Tom Bagby. (2020). "Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis." Web.
1. Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad, Daisy Stanton, David Kao, Matt Shannon, Tom Bagby. Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5324

Generative pre-training for speech with autoregressive predictive coding

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Authors:
Yu-An Chung, James Glass
Submitted On:
14 May 2020 - 5:56pm
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icassp-20.generative.slides.pdf

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[1] Yu-An Chung, James Glass, "Generative pre-training for speech with autoregressive predictive coding", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5323. Accessed: Jul. 06, 2020.
@article{5323-20,
url = {http://sigport.org/5323},
author = {Yu-An Chung; James Glass },
publisher = {IEEE SigPort},
title = {Generative pre-training for speech with autoregressive predictive coding},
year = {2020} }
TY - EJOUR
T1 - Generative pre-training for speech with autoregressive predictive coding
AU - Yu-An Chung; James Glass
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5323
ER -
Yu-An Chung, James Glass. (2020). Generative pre-training for speech with autoregressive predictive coding. IEEE SigPort. http://sigport.org/5323
Yu-An Chung, James Glass, 2020. Generative pre-training for speech with autoregressive predictive coding. Available at: http://sigport.org/5323.
Yu-An Chung, James Glass. (2020). "Generative pre-training for speech with autoregressive predictive coding." Web.
1. Yu-An Chung, James Glass. Generative pre-training for speech with autoregressive predictive coding [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5323

MANet: Multi-Scale Aggregated Network For Light Field Depth Estimation

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Authors:
Yan Li, Lu Zhang, Qiong Wang, Gauthier Lafruit
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14 May 2020 - 4:54pm
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Slides_Yan LI_ICASSP2020.pdf

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[1] Yan Li, Lu Zhang, Qiong Wang, Gauthier Lafruit, "MANet: Multi-Scale Aggregated Network For Light Field Depth Estimation", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5322. Accessed: Jul. 06, 2020.
@article{5322-20,
url = {http://sigport.org/5322},
author = {Yan Li; Lu Zhang; Qiong Wang; Gauthier Lafruit },
publisher = {IEEE SigPort},
title = {MANet: Multi-Scale Aggregated Network For Light Field Depth Estimation},
year = {2020} }
TY - EJOUR
T1 - MANet: Multi-Scale Aggregated Network For Light Field Depth Estimation
AU - Yan Li; Lu Zhang; Qiong Wang; Gauthier Lafruit
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5322
ER -
Yan Li, Lu Zhang, Qiong Wang, Gauthier Lafruit. (2020). MANet: Multi-Scale Aggregated Network For Light Field Depth Estimation. IEEE SigPort. http://sigport.org/5322
Yan Li, Lu Zhang, Qiong Wang, Gauthier Lafruit, 2020. MANet: Multi-Scale Aggregated Network For Light Field Depth Estimation. Available at: http://sigport.org/5322.
Yan Li, Lu Zhang, Qiong Wang, Gauthier Lafruit. (2020). "MANet: Multi-Scale Aggregated Network For Light Field Depth Estimation." Web.
1. Yan Li, Lu Zhang, Qiong Wang, Gauthier Lafruit. MANet: Multi-Scale Aggregated Network For Light Field Depth Estimation [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5322

Blind Multi-Spectral Image Pan-Sharpening


We address the problem of sharpening low spatial-resolution multi-spectral (MS) images with their associated misaligned high spatial-resolution panchromatic (PAN) image, based on priors on the spatial blur kernel and on the cross-channel relationship. In particular, we formulate the blind pan-sharpening problem within a multi-convex optimization framework using total generalized variation for the blur kernel and local Laplacian prior for the cross-channel relationship.

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Authors:
Lantao Yu, Dehong Liu, Hassan Mansour, Petros Boufounos, Yanting Ma
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14 May 2020 - 5:01pm
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icassp2020_present.pdf

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ICASSP2020_CI-L1.1_Slide.pdf

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[1] Lantao Yu, Dehong Liu, Hassan Mansour, Petros Boufounos, Yanting Ma, "Blind Multi-Spectral Image Pan-Sharpening", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5321. Accessed: Jul. 06, 2020.
@article{5321-20,
url = {http://sigport.org/5321},
author = {Lantao Yu; Dehong Liu; Hassan Mansour; Petros Boufounos; Yanting Ma },
publisher = {IEEE SigPort},
title = {Blind Multi-Spectral Image Pan-Sharpening},
year = {2020} }
TY - EJOUR
T1 - Blind Multi-Spectral Image Pan-Sharpening
AU - Lantao Yu; Dehong Liu; Hassan Mansour; Petros Boufounos; Yanting Ma
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5321
ER -
Lantao Yu, Dehong Liu, Hassan Mansour, Petros Boufounos, Yanting Ma. (2020). Blind Multi-Spectral Image Pan-Sharpening. IEEE SigPort. http://sigport.org/5321
Lantao Yu, Dehong Liu, Hassan Mansour, Petros Boufounos, Yanting Ma, 2020. Blind Multi-Spectral Image Pan-Sharpening. Available at: http://sigport.org/5321.
Lantao Yu, Dehong Liu, Hassan Mansour, Petros Boufounos, Yanting Ma. (2020). "Blind Multi-Spectral Image Pan-Sharpening." Web.
1. Lantao Yu, Dehong Liu, Hassan Mansour, Petros Boufounos, Yanting Ma. Blind Multi-Spectral Image Pan-Sharpening [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5321

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