Sorry, you need to enable JavaScript to visit this website.

Image/Video Processing

Single Image Interpolation Exploiting Semi-local Similarity


This paper explores the modeling and exploitation of semi-local similarity in natural images to address the ill-posed nature of image interpolation. Our approach distinguishes itself from prior approaches by direct and careful use of semi-local similar patches to interpolate each individual patch. Our work uses a simple, parallelizable algorithm without the need to solve complicated optimization problems. Experimental results demonstrate that our interpolated images achieve significantly higher objective and subjective quality compared with those from state-of-the-art algorithms.

Paper Details

Authors:
Submitted On:
16 May 2019 - 8:32pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Single Image Interpolation Exploiting Semi-local Similarity.pdf

(5)

Subscribe

[1] , "Single Image Interpolation Exploiting Semi-local Similarity", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4542. Accessed: May. 21, 2019.
@article{4542-19,
url = {http://sigport.org/4542},
author = { },
publisher = {IEEE SigPort},
title = {Single Image Interpolation Exploiting Semi-local Similarity},
year = {2019} }
TY - EJOUR
T1 - Single Image Interpolation Exploiting Semi-local Similarity
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4542
ER -
. (2019). Single Image Interpolation Exploiting Semi-local Similarity. IEEE SigPort. http://sigport.org/4542
, 2019. Single Image Interpolation Exploiting Semi-local Similarity. Available at: http://sigport.org/4542.
. (2019). "Single Image Interpolation Exploiting Semi-local Similarity." Web.
1. . Single Image Interpolation Exploiting Semi-local Similarity [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4542

ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS


In this paper we compare the quality of synthesized views produced by four DIBR methods when fed by depth maps estimated by five state-of-the-art stereo matching algorithms. Also, we compute the correlation between four popular metrics for ranking stereo matching algorithms and two metrics commonly used to evaluate synthesized views (PSNR and SSIM) plus one specific for DIBR.

Paper Details

Authors:
Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung
Submitted On:
13 May 2019 - 9:19pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS

(5)

Subscribe

[1] Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung, "ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4499. Accessed: May. 21, 2019.
@article{4499-19,
url = {http://sigport.org/4499},
author = {Adriano Quilião de Oliveira; Thiago Lopes Trugillo da Silveira; Marcelo Walter; Cláudio Rosito Jung },
publisher = {IEEE SigPort},
title = {ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS},
year = {2019} }
TY - EJOUR
T1 - ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS
AU - Adriano Quilião de Oliveira; Thiago Lopes Trugillo da Silveira; Marcelo Walter; Cláudio Rosito Jung
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4499
ER -
Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung. (2019). ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS. IEEE SigPort. http://sigport.org/4499
Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung, 2019. ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS. Available at: http://sigport.org/4499.
Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung. (2019). "ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS." Web.
1. Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung. ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4499

MULTI-FRAME SUPER-RESOLUTION FOR TIME-OF-FLIGHT IMAGING

Paper Details

Authors:
Pablo Ruiz, Oliver Cossairt, Aggelos Katsaggelos
Submitted On:
12 May 2019 - 5:16am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

ICASSP_2019_v4.pdf

(2)

Subscribe

[1] Pablo Ruiz, Oliver Cossairt, Aggelos Katsaggelos, "MULTI-FRAME SUPER-RESOLUTION FOR TIME-OF-FLIGHT IMAGING", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4461. Accessed: May. 21, 2019.
@article{4461-19,
url = {http://sigport.org/4461},
author = {Pablo Ruiz; Oliver Cossairt; Aggelos Katsaggelos },
publisher = {IEEE SigPort},
title = {MULTI-FRAME SUPER-RESOLUTION FOR TIME-OF-FLIGHT IMAGING},
year = {2019} }
TY - EJOUR
T1 - MULTI-FRAME SUPER-RESOLUTION FOR TIME-OF-FLIGHT IMAGING
AU - Pablo Ruiz; Oliver Cossairt; Aggelos Katsaggelos
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4461
ER -
Pablo Ruiz, Oliver Cossairt, Aggelos Katsaggelos. (2019). MULTI-FRAME SUPER-RESOLUTION FOR TIME-OF-FLIGHT IMAGING. IEEE SigPort. http://sigport.org/4461
Pablo Ruiz, Oliver Cossairt, Aggelos Katsaggelos, 2019. MULTI-FRAME SUPER-RESOLUTION FOR TIME-OF-FLIGHT IMAGING. Available at: http://sigport.org/4461.
Pablo Ruiz, Oliver Cossairt, Aggelos Katsaggelos. (2019). "MULTI-FRAME SUPER-RESOLUTION FOR TIME-OF-FLIGHT IMAGING." Web.
1. Pablo Ruiz, Oliver Cossairt, Aggelos Katsaggelos. MULTI-FRAME SUPER-RESOLUTION FOR TIME-OF-FLIGHT IMAGING [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4461

Optimal Feature Selection for Blind Super-Resolution Image Quality Evaluation


The visual quality of images resulting from Super Resolution (SR) techniques is predicted with blind image quality assessment (BIQA) models trained on a database(s) of human rated distorted images and associated human subjective opinion scores. Such opinion-aware (OA) methods need a large amount of training samples with associated human subjective scores, which are scarce in the field of SR. By contrast, opinion distortion unaware (ODU) methods do not need human subjective scores for training.

Paper Details

Authors:
Juan Berón, Hernán Darío Benítez Restrepo, Alan C. Bovik
Submitted On:
11 May 2019 - 3:49pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

OPTIMAL_FEATURE_SELECTION_FOR_BLIND_SUPER-RESOLUTION_IMAGE_QUALITY_EVALUATION

(2)

Subscribe

[1] Juan Berón, Hernán Darío Benítez Restrepo, Alan C. Bovik, "Optimal Feature Selection for Blind Super-Resolution Image Quality Evaluation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4451. Accessed: May. 21, 2019.
@article{4451-19,
url = {http://sigport.org/4451},
author = {Juan Berón; Hernán Darío Benítez Restrepo; Alan C. Bovik },
publisher = {IEEE SigPort},
title = {Optimal Feature Selection for Blind Super-Resolution Image Quality Evaluation},
year = {2019} }
TY - EJOUR
T1 - Optimal Feature Selection for Blind Super-Resolution Image Quality Evaluation
AU - Juan Berón; Hernán Darío Benítez Restrepo; Alan C. Bovik
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4451
ER -
Juan Berón, Hernán Darío Benítez Restrepo, Alan C. Bovik. (2019). Optimal Feature Selection for Blind Super-Resolution Image Quality Evaluation. IEEE SigPort. http://sigport.org/4451
Juan Berón, Hernán Darío Benítez Restrepo, Alan C. Bovik, 2019. Optimal Feature Selection for Blind Super-Resolution Image Quality Evaluation. Available at: http://sigport.org/4451.
Juan Berón, Hernán Darío Benítez Restrepo, Alan C. Bovik. (2019). "Optimal Feature Selection for Blind Super-Resolution Image Quality Evaluation." Web.
1. Juan Berón, Hernán Darío Benítez Restrepo, Alan C. Bovik. Optimal Feature Selection for Blind Super-Resolution Image Quality Evaluation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4451

Scene Privacy Protection


Uploading pictures to a cloud service may reveal, through automatic inference, scene information that a user might want to keep private. To protect images from automatic scene classification, we present a method that misleads the classifier while introducing only a minimal distortion and limiting the likelihood that the ground-truth class can be inferred from the processed image. The method, based on the Fast Gradient Sign Method (FGSM), generates adversarial images and leverages a multi-class scene classifier trained to select a target scene class.

Paper Details

Authors:
Chau Yi Li, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon, Andrea Cavallaro
Submitted On:
11 May 2019 - 11:52am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

ICASSP_poster.pdf

(15)

Subscribe

[1] Chau Yi Li, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon, Andrea Cavallaro, "Scene Privacy Protection", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4447. Accessed: May. 21, 2019.
@article{4447-19,
url = {http://sigport.org/4447},
author = {Chau Yi Li; Ali Shahin Shamsabadi; Ricardo Sanchez-Matilla; Riccardo Mazzon; Andrea Cavallaro },
publisher = {IEEE SigPort},
title = {Scene Privacy Protection},
year = {2019} }
TY - EJOUR
T1 - Scene Privacy Protection
AU - Chau Yi Li; Ali Shahin Shamsabadi; Ricardo Sanchez-Matilla; Riccardo Mazzon; Andrea Cavallaro
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4447
ER -
Chau Yi Li, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon, Andrea Cavallaro. (2019). Scene Privacy Protection. IEEE SigPort. http://sigport.org/4447
Chau Yi Li, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon, Andrea Cavallaro, 2019. Scene Privacy Protection. Available at: http://sigport.org/4447.
Chau Yi Li, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon, Andrea Cavallaro. (2019). "Scene Privacy Protection." Web.
1. Chau Yi Li, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon, Andrea Cavallaro. Scene Privacy Protection [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4447

Adaptive Scenario Discovery for Crowd Counting


Crowd counting, i.e., estimation number of the pedestrian in crowd images, is emerging as an important research problem
with the public security applications. A key component for the crowd counting systems is the construction of counting
models which are robust to various scenarios under facts such as camera perspective and physical barriers. In this paper,
we present an adaptive scenario discovery framework for crowd counting. The system is structured with two parallel

Paper Details

Authors:
Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He
Submitted On:
11 May 2019 - 5:40am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

icassp_poster_v1.1.pdf

(12)

Subscribe

[1] Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He, "Adaptive Scenario Discovery for Crowd Counting", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4440. Accessed: May. 21, 2019.
@article{4440-19,
url = {http://sigport.org/4440},
author = {Yingbin Zheng; Hao Ye; Wenxin Hu; Jing Yang; Liang He },
publisher = {IEEE SigPort},
title = {Adaptive Scenario Discovery for Crowd Counting},
year = {2019} }
TY - EJOUR
T1 - Adaptive Scenario Discovery for Crowd Counting
AU - Yingbin Zheng; Hao Ye; Wenxin Hu; Jing Yang; Liang He
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4440
ER -
Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He. (2019). Adaptive Scenario Discovery for Crowd Counting. IEEE SigPort. http://sigport.org/4440
Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He, 2019. Adaptive Scenario Discovery for Crowd Counting. Available at: http://sigport.org/4440.
Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He. (2019). "Adaptive Scenario Discovery for Crowd Counting." Web.
1. Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He. Adaptive Scenario Discovery for Crowd Counting [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4440

Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques


We present recently developed computational techniques that exploit spectral geometry of the energy spectra for differential energy flux over MAVEN data sets. The goal is to enable a large scale automated discovery detection of statistical analysis of ion trails in the Martian atmosphere. Specifically, we present a case study across a diverse portfolio of azimuthal (φ) and polar (θ) angles over the same time frame and demonstrate that angular separation helps us to distinguish between individual ion escape processes.

Paper Details

Authors:
Qiutong Jin, Ananya Sen Gupta, Mirela Kapo, Emma Hawk, Jasper Halekas
Submitted On:
10 May 2019 - 11:24pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster:Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques

(9)

Subscribe

[1] Qiutong Jin, Ananya Sen Gupta, Mirela Kapo, Emma Hawk, Jasper Halekas, "Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4431. Accessed: May. 21, 2019.
@article{4431-19,
url = {http://sigport.org/4431},
author = {Qiutong Jin; Ananya Sen Gupta; Mirela Kapo; Emma Hawk; Jasper Halekas },
publisher = {IEEE SigPort},
title = {Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques},
year = {2019} }
TY - EJOUR
T1 - Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques
AU - Qiutong Jin; Ananya Sen Gupta; Mirela Kapo; Emma Hawk; Jasper Halekas
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4431
ER -
Qiutong Jin, Ananya Sen Gupta, Mirela Kapo, Emma Hawk, Jasper Halekas. (2019). Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques. IEEE SigPort. http://sigport.org/4431
Qiutong Jin, Ananya Sen Gupta, Mirela Kapo, Emma Hawk, Jasper Halekas, 2019. Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques. Available at: http://sigport.org/4431.
Qiutong Jin, Ananya Sen Gupta, Mirela Kapo, Emma Hawk, Jasper Halekas. (2019). "Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques." Web.
1. Qiutong Jin, Ananya Sen Gupta, Mirela Kapo, Emma Hawk, Jasper Halekas. Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4431

Blind Denoising of Mixed Gaussian-Impulse Noise by Single CNN

Paper Details

Authors:
Ryo Abiko, Masaaki Ikehara
Submitted On:
14 May 2019 - 1:21am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

icassp_denoise.pdf

(4)

Subscribe

[1] Ryo Abiko, Masaaki Ikehara, "Blind Denoising of Mixed Gaussian-Impulse Noise by Single CNN", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4378. Accessed: May. 21, 2019.
@article{4378-19,
url = {http://sigport.org/4378},
author = {Ryo Abiko; Masaaki Ikehara },
publisher = {IEEE SigPort},
title = {Blind Denoising of Mixed Gaussian-Impulse Noise by Single CNN},
year = {2019} }
TY - EJOUR
T1 - Blind Denoising of Mixed Gaussian-Impulse Noise by Single CNN
AU - Ryo Abiko; Masaaki Ikehara
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4378
ER -
Ryo Abiko, Masaaki Ikehara. (2019). Blind Denoising of Mixed Gaussian-Impulse Noise by Single CNN. IEEE SigPort. http://sigport.org/4378
Ryo Abiko, Masaaki Ikehara, 2019. Blind Denoising of Mixed Gaussian-Impulse Noise by Single CNN. Available at: http://sigport.org/4378.
Ryo Abiko, Masaaki Ikehara. (2019). "Blind Denoising of Mixed Gaussian-Impulse Noise by Single CNN." Web.
1. Ryo Abiko, Masaaki Ikehara. Blind Denoising of Mixed Gaussian-Impulse Noise by Single CNN [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4378

Adaptive Graph Formulation for 3D Shape Representation


3D shape recognition has attracted a great interest in computer vision due to its large number of important and exciting applications. This has led to exploring a variety of approaches to develop more efficient 3D analysis methods. However, current works take into account descriptions of global shape to generate models, ignoring small differences causing the problem of mismatching, especially for high similarity shapes.

Paper Details

Authors:
Basheer Alwaely and Charith Abhayaratne
Submitted On:
10 May 2019 - 11:13am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster at ICASSP 2019

(4)

Keywords

Additional Categories

Subscribe

[1] Basheer Alwaely and Charith Abhayaratne, "Adaptive Graph Formulation for 3D Shape Representation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4361. Accessed: May. 21, 2019.
@article{4361-19,
url = {http://sigport.org/4361},
author = {Basheer Alwaely and Charith Abhayaratne },
publisher = {IEEE SigPort},
title = {Adaptive Graph Formulation for 3D Shape Representation},
year = {2019} }
TY - EJOUR
T1 - Adaptive Graph Formulation for 3D Shape Representation
AU - Basheer Alwaely and Charith Abhayaratne
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4361
ER -
Basheer Alwaely and Charith Abhayaratne. (2019). Adaptive Graph Formulation for 3D Shape Representation. IEEE SigPort. http://sigport.org/4361
Basheer Alwaely and Charith Abhayaratne, 2019. Adaptive Graph Formulation for 3D Shape Representation. Available at: http://sigport.org/4361.
Basheer Alwaely and Charith Abhayaratne. (2019). "Adaptive Graph Formulation for 3D Shape Representation." Web.
1. Basheer Alwaely and Charith Abhayaratne. Adaptive Graph Formulation for 3D Shape Representation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4361

IMAGE DEMOSAICKING VIA CHROMINANCE IMAGES WITH PARALLEL CONVOLUTIONAL NEURAL NETWORKS


Many conventional demosaicking methods are based on hand-crafted filters. However, the filters yield false colors in salient regions like edges and textures. For acquisition of high quality images, we focus on neural networks. Neural networks lead to high accuracy in many fields. However, there are few methods in demosaicking field. For adaptation to demosaicking, we consider not only network's architecture but also the input. In this research, we utilize a Bayer image as input of our networks.

Paper Details

Authors:
Takuro Yamaguchi, Masaaki Ikehara
Submitted On:
10 May 2019 - 11:13am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICASSP2019_presentation.pptx

(13)

Subscribe

[1] Takuro Yamaguchi, Masaaki Ikehara, "IMAGE DEMOSAICKING VIA CHROMINANCE IMAGES WITH PARALLEL CONVOLUTIONAL NEURAL NETWORKS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4360. Accessed: May. 21, 2019.
@article{4360-19,
url = {http://sigport.org/4360},
author = {Takuro Yamaguchi; Masaaki Ikehara },
publisher = {IEEE SigPort},
title = {IMAGE DEMOSAICKING VIA CHROMINANCE IMAGES WITH PARALLEL CONVOLUTIONAL NEURAL NETWORKS},
year = {2019} }
TY - EJOUR
T1 - IMAGE DEMOSAICKING VIA CHROMINANCE IMAGES WITH PARALLEL CONVOLUTIONAL NEURAL NETWORKS
AU - Takuro Yamaguchi; Masaaki Ikehara
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4360
ER -
Takuro Yamaguchi, Masaaki Ikehara. (2019). IMAGE DEMOSAICKING VIA CHROMINANCE IMAGES WITH PARALLEL CONVOLUTIONAL NEURAL NETWORKS. IEEE SigPort. http://sigport.org/4360
Takuro Yamaguchi, Masaaki Ikehara, 2019. IMAGE DEMOSAICKING VIA CHROMINANCE IMAGES WITH PARALLEL CONVOLUTIONAL NEURAL NETWORKS. Available at: http://sigport.org/4360.
Takuro Yamaguchi, Masaaki Ikehara. (2019). "IMAGE DEMOSAICKING VIA CHROMINANCE IMAGES WITH PARALLEL CONVOLUTIONAL NEURAL NETWORKS." Web.
1. Takuro Yamaguchi, Masaaki Ikehara. IMAGE DEMOSAICKING VIA CHROMINANCE IMAGES WITH PARALLEL CONVOLUTIONAL NEURAL NETWORKS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4360

Pages