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Machine Learning for Signal Processing

Outlier-Robust Matrix Completion via lp-Minimization


Matrix completion refers to the recovery of a low‐rank matrix from only a subset of its possibly noisy entries, and has a variety of important applications such as collaborative filtering, image inpainting and restoration, system identification, node localization and genotype imputation. It is because many real-world signals can be approximated by a matrix whose rank is much smaller than the row and column numbers. Most techniques for matrix completion in the literature assume Gaussian noise and thus they are not robust to outliers.

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Authors:
Wen-Jun Zeng, Hing Cheung So
Submitted On:
2 March 2018 - 1:57am
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rmp.pdf

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[1] Wen-Jun Zeng, Hing Cheung So, "Outlier-Robust Matrix Completion via lp-Minimization", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2373. Accessed: Aug. 21, 2018.
@article{2373-18,
url = {http://sigport.org/2373},
author = {Wen-Jun Zeng; Hing Cheung So },
publisher = {IEEE SigPort},
title = {Outlier-Robust Matrix Completion via lp-Minimization},
year = {2018} }
TY - EJOUR
T1 - Outlier-Robust Matrix Completion via lp-Minimization
AU - Wen-Jun Zeng; Hing Cheung So
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2373
ER -
Wen-Jun Zeng, Hing Cheung So. (2018). Outlier-Robust Matrix Completion via lp-Minimization. IEEE SigPort. http://sigport.org/2373
Wen-Jun Zeng, Hing Cheung So, 2018. Outlier-Robust Matrix Completion via lp-Minimization. Available at: http://sigport.org/2373.
Wen-Jun Zeng, Hing Cheung So. (2018). "Outlier-Robust Matrix Completion via lp-Minimization." Web.
1. Wen-Jun Zeng, Hing Cheung So. Outlier-Robust Matrix Completion via lp-Minimization [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2373

ASSESSING THE PROGNOSTIC IMPACT OF 3D CT IMAGE TUMOUR RIND TEXTURE FEATURES ON LUNG CANCER SURVIVAL MODELLING


In this paper we examine a technique for developing prognostic image characteristics, termed radiomics, for non-small cell lung cancer based on a tumour edge region-based analysis. Texture features were extracted from the rind of the tumour in a publicly available 3D CT data set to predict two-year survival. The derived models were compared against the previous methods of training radiomic signatures that are descriptive of the whole tumour volume. Radiomic features derived solely from regions external, but neighbouring, the tumour were shown to also have prognostic value.

Paper Details

Authors:
Alanna Vial, David Stirling, Matthew Field, Montserrat Ros, Christian Ritz, Martin Carolan, Lois Hollowayn, Alexis A. Miller
Submitted On:
11 December 2017 - 5:01pm
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GlobalSIP - Conference Presentation v2.pdf

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[1] Alanna Vial, David Stirling, Matthew Field, Montserrat Ros, Christian Ritz, Martin Carolan, Lois Hollowayn, Alexis A. Miller, "ASSESSING THE PROGNOSTIC IMPACT OF 3D CT IMAGE TUMOUR RIND TEXTURE FEATURES ON LUNG CANCER SURVIVAL MODELLING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2371. Accessed: Aug. 21, 2018.
@article{2371-17,
url = {http://sigport.org/2371},
author = {Alanna Vial; David Stirling; Matthew Field; Montserrat Ros; Christian Ritz; Martin Carolan; Lois Hollowayn; Alexis A. Miller },
publisher = {IEEE SigPort},
title = {ASSESSING THE PROGNOSTIC IMPACT OF 3D CT IMAGE TUMOUR RIND TEXTURE FEATURES ON LUNG CANCER SURVIVAL MODELLING},
year = {2017} }
TY - EJOUR
T1 - ASSESSING THE PROGNOSTIC IMPACT OF 3D CT IMAGE TUMOUR RIND TEXTURE FEATURES ON LUNG CANCER SURVIVAL MODELLING
AU - Alanna Vial; David Stirling; Matthew Field; Montserrat Ros; Christian Ritz; Martin Carolan; Lois Hollowayn; Alexis A. Miller
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2371
ER -
Alanna Vial, David Stirling, Matthew Field, Montserrat Ros, Christian Ritz, Martin Carolan, Lois Hollowayn, Alexis A. Miller. (2017). ASSESSING THE PROGNOSTIC IMPACT OF 3D CT IMAGE TUMOUR RIND TEXTURE FEATURES ON LUNG CANCER SURVIVAL MODELLING. IEEE SigPort. http://sigport.org/2371
Alanna Vial, David Stirling, Matthew Field, Montserrat Ros, Christian Ritz, Martin Carolan, Lois Hollowayn, Alexis A. Miller, 2017. ASSESSING THE PROGNOSTIC IMPACT OF 3D CT IMAGE TUMOUR RIND TEXTURE FEATURES ON LUNG CANCER SURVIVAL MODELLING. Available at: http://sigport.org/2371.
Alanna Vial, David Stirling, Matthew Field, Montserrat Ros, Christian Ritz, Martin Carolan, Lois Hollowayn, Alexis A. Miller. (2017). "ASSESSING THE PROGNOSTIC IMPACT OF 3D CT IMAGE TUMOUR RIND TEXTURE FEATURES ON LUNG CANCER SURVIVAL MODELLING." Web.
1. Alanna Vial, David Stirling, Matthew Field, Montserrat Ros, Christian Ritz, Martin Carolan, Lois Hollowayn, Alexis A. Miller. ASSESSING THE PROGNOSTIC IMPACT OF 3D CT IMAGE TUMOUR RIND TEXTURE FEATURES ON LUNG CANCER SURVIVAL MODELLING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2371

Adaptive Basis Selection for Compressed Sensing in Robotic Tactile Skins

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Authors:
Brayden Hollis, Stacy Patterson, Jeff Trinkle
Submitted On:
14 November 2017 - 12:55pm
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GlobalSIP_Poster.pdf

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[1] Brayden Hollis, Stacy Patterson, Jeff Trinkle, "Adaptive Basis Selection for Compressed Sensing in Robotic Tactile Skins", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2351. Accessed: Aug. 21, 2018.
@article{2351-17,
url = {http://sigport.org/2351},
author = {Brayden Hollis; Stacy Patterson; Jeff Trinkle },
publisher = {IEEE SigPort},
title = {Adaptive Basis Selection for Compressed Sensing in Robotic Tactile Skins},
year = {2017} }
TY - EJOUR
T1 - Adaptive Basis Selection for Compressed Sensing in Robotic Tactile Skins
AU - Brayden Hollis; Stacy Patterson; Jeff Trinkle
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2351
ER -
Brayden Hollis, Stacy Patterson, Jeff Trinkle. (2017). Adaptive Basis Selection for Compressed Sensing in Robotic Tactile Skins. IEEE SigPort. http://sigport.org/2351
Brayden Hollis, Stacy Patterson, Jeff Trinkle, 2017. Adaptive Basis Selection for Compressed Sensing in Robotic Tactile Skins. Available at: http://sigport.org/2351.
Brayden Hollis, Stacy Patterson, Jeff Trinkle. (2017). "Adaptive Basis Selection for Compressed Sensing in Robotic Tactile Skins." Web.
1. Brayden Hollis, Stacy Patterson, Jeff Trinkle. Adaptive Basis Selection for Compressed Sensing in Robotic Tactile Skins [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2351

Cepstrum Coefficients Based Sleep Stage Classification

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Authors:
Emin Argun Oral, Muhammet Mustafa Codur, Ibrahim Yucel Ozbek
Submitted On:
14 November 2017 - 10:10am
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Cepstrum Coefficients Sleep Classification

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[1] Emin Argun Oral, Muhammet Mustafa Codur, Ibrahim Yucel Ozbek, "Cepstrum Coefficients Based Sleep Stage Classification", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2344. Accessed: Aug. 21, 2018.
@article{2344-17,
url = {http://sigport.org/2344},
author = {Emin Argun Oral; Muhammet Mustafa Codur; Ibrahim Yucel Ozbek },
publisher = {IEEE SigPort},
title = {Cepstrum Coefficients Based Sleep Stage Classification},
year = {2017} }
TY - EJOUR
T1 - Cepstrum Coefficients Based Sleep Stage Classification
AU - Emin Argun Oral; Muhammet Mustafa Codur; Ibrahim Yucel Ozbek
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2344
ER -
Emin Argun Oral, Muhammet Mustafa Codur, Ibrahim Yucel Ozbek. (2017). Cepstrum Coefficients Based Sleep Stage Classification. IEEE SigPort. http://sigport.org/2344
Emin Argun Oral, Muhammet Mustafa Codur, Ibrahim Yucel Ozbek, 2017. Cepstrum Coefficients Based Sleep Stage Classification. Available at: http://sigport.org/2344.
Emin Argun Oral, Muhammet Mustafa Codur, Ibrahim Yucel Ozbek. (2017). "Cepstrum Coefficients Based Sleep Stage Classification." Web.
1. Emin Argun Oral, Muhammet Mustafa Codur, Ibrahim Yucel Ozbek. Cepstrum Coefficients Based Sleep Stage Classification [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2344

COMBINATORIAL MULTI-ARMED BANDIT PROBLEM WITH PROBABILISTICALLY TRIGGERED ARMS: A CASE WITH BOUNDED REGRET

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Authors:
A. Omer Saritac, C. Tekin
Submitted On:
14 November 2017 - 7:11am
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presentation_1.pdf

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[1] A. Omer Saritac, C. Tekin, "COMBINATORIAL MULTI-ARMED BANDIT PROBLEM WITH PROBABILISTICALLY TRIGGERED ARMS: A CASE WITH BOUNDED REGRET", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2342. Accessed: Aug. 21, 2018.
@article{2342-17,
url = {http://sigport.org/2342},
author = {A. Omer Saritac; C. Tekin },
publisher = {IEEE SigPort},
title = {COMBINATORIAL MULTI-ARMED BANDIT PROBLEM WITH PROBABILISTICALLY TRIGGERED ARMS: A CASE WITH BOUNDED REGRET},
year = {2017} }
TY - EJOUR
T1 - COMBINATORIAL MULTI-ARMED BANDIT PROBLEM WITH PROBABILISTICALLY TRIGGERED ARMS: A CASE WITH BOUNDED REGRET
AU - A. Omer Saritac; C. Tekin
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2342
ER -
A. Omer Saritac, C. Tekin. (2017). COMBINATORIAL MULTI-ARMED BANDIT PROBLEM WITH PROBABILISTICALLY TRIGGERED ARMS: A CASE WITH BOUNDED REGRET. IEEE SigPort. http://sigport.org/2342
A. Omer Saritac, C. Tekin, 2017. COMBINATORIAL MULTI-ARMED BANDIT PROBLEM WITH PROBABILISTICALLY TRIGGERED ARMS: A CASE WITH BOUNDED REGRET. Available at: http://sigport.org/2342.
A. Omer Saritac, C. Tekin. (2017). "COMBINATORIAL MULTI-ARMED BANDIT PROBLEM WITH PROBABILISTICALLY TRIGGERED ARMS: A CASE WITH BOUNDED REGRET." Web.
1. A. Omer Saritac, C. Tekin. COMBINATORIAL MULTI-ARMED BANDIT PROBLEM WITH PROBABILISTICALLY TRIGGERED ARMS: A CASE WITH BOUNDED REGRET [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2342

Generating Forbidden Region Virtual Fixtures By Classification of Movement Intention Based on Event-Related Desynchronization


The development of children’s cognitive and perceptual skills depends heavily on object exploration and manipulative experiences. New types of robotic assistive technologies that enable children with disabilities to interact with their environment, which prove to be beneficial for their cognitive and perceptual skills development, have emerged in recent years. In this study, a human-robot interface that uses Event-Related Desynchronization (ERD) brain response during movement was developed.

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12 November 2017 - 10:57pm
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2017 GlobalSIP slide.pdf

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[1] , "Generating Forbidden Region Virtual Fixtures By Classification of Movement Intention Based on Event-Related Desynchronization", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2317. Accessed: Aug. 21, 2018.
@article{2317-17,
url = {http://sigport.org/2317},
author = { },
publisher = {IEEE SigPort},
title = {Generating Forbidden Region Virtual Fixtures By Classification of Movement Intention Based on Event-Related Desynchronization},
year = {2017} }
TY - EJOUR
T1 - Generating Forbidden Region Virtual Fixtures By Classification of Movement Intention Based on Event-Related Desynchronization
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2317
ER -
. (2017). Generating Forbidden Region Virtual Fixtures By Classification of Movement Intention Based on Event-Related Desynchronization. IEEE SigPort. http://sigport.org/2317
, 2017. Generating Forbidden Region Virtual Fixtures By Classification of Movement Intention Based on Event-Related Desynchronization. Available at: http://sigport.org/2317.
. (2017). "Generating Forbidden Region Virtual Fixtures By Classification of Movement Intention Based on Event-Related Desynchronization." Web.
1. . Generating Forbidden Region Virtual Fixtures By Classification of Movement Intention Based on Event-Related Desynchronization [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2317

End-To-End Chinese Text Recognition

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Authors:
Jie Hu, Tszhang Guo, Ji Cao, Changshui Zhang
Submitted On:
11 November 2017 - 12:19am
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presentation at GlobalSIP

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[1] Jie Hu, Tszhang Guo, Ji Cao, Changshui Zhang, "End-To-End Chinese Text Recognition", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2304. Accessed: Aug. 21, 2018.
@article{2304-17,
url = {http://sigport.org/2304},
author = {Jie Hu; Tszhang Guo; Ji Cao; Changshui Zhang },
publisher = {IEEE SigPort},
title = {End-To-End Chinese Text Recognition},
year = {2017} }
TY - EJOUR
T1 - End-To-End Chinese Text Recognition
AU - Jie Hu; Tszhang Guo; Ji Cao; Changshui Zhang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2304
ER -
Jie Hu, Tszhang Guo, Ji Cao, Changshui Zhang. (2017). End-To-End Chinese Text Recognition. IEEE SigPort. http://sigport.org/2304
Jie Hu, Tszhang Guo, Ji Cao, Changshui Zhang, 2017. End-To-End Chinese Text Recognition. Available at: http://sigport.org/2304.
Jie Hu, Tszhang Guo, Ji Cao, Changshui Zhang. (2017). "End-To-End Chinese Text Recognition." Web.
1. Jie Hu, Tszhang Guo, Ji Cao, Changshui Zhang. End-To-End Chinese Text Recognition [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2304

Poster for GlobalSIP 2017 Paper #1180: The Impact of Sports Sentiment on Stock Returns: A Case Study from Professional Sports Leagues

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Authors:
QINGLIANG FAN; WENWEN LEI; XIAP-PING ZHANG
Submitted On:
9 November 2017 - 10:15pm
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poster.pdf

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[1] QINGLIANG FAN; WENWEN LEI; XIAP-PING ZHANG, "Poster for GlobalSIP 2017 Paper #1180: The Impact of Sports Sentiment on Stock Returns: A Case Study from Professional Sports Leagues", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2280. Accessed: Aug. 21, 2018.
@article{2280-17,
url = {http://sigport.org/2280},
author = {QINGLIANG FAN; WENWEN LEI; XIAP-PING ZHANG },
publisher = {IEEE SigPort},
title = {Poster for GlobalSIP 2017 Paper #1180: The Impact of Sports Sentiment on Stock Returns: A Case Study from Professional Sports Leagues},
year = {2017} }
TY - EJOUR
T1 - Poster for GlobalSIP 2017 Paper #1180: The Impact of Sports Sentiment on Stock Returns: A Case Study from Professional Sports Leagues
AU - QINGLIANG FAN; WENWEN LEI; XIAP-PING ZHANG
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2280
ER -
QINGLIANG FAN; WENWEN LEI; XIAP-PING ZHANG. (2017). Poster for GlobalSIP 2017 Paper #1180: The Impact of Sports Sentiment on Stock Returns: A Case Study from Professional Sports Leagues. IEEE SigPort. http://sigport.org/2280
QINGLIANG FAN; WENWEN LEI; XIAP-PING ZHANG, 2017. Poster for GlobalSIP 2017 Paper #1180: The Impact of Sports Sentiment on Stock Returns: A Case Study from Professional Sports Leagues. Available at: http://sigport.org/2280.
QINGLIANG FAN; WENWEN LEI; XIAP-PING ZHANG. (2017). "Poster for GlobalSIP 2017 Paper #1180: The Impact of Sports Sentiment on Stock Returns: A Case Study from Professional Sports Leagues." Web.
1. QINGLIANG FAN; WENWEN LEI; XIAP-PING ZHANG. Poster for GlobalSIP 2017 Paper #1180: The Impact of Sports Sentiment on Stock Returns: A Case Study from Professional Sports Leagues [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2280

Sparse Modeling in Image Processing and Deep Learning (Keynote Talk)


Sparse approximation is a well-established theory, with a profound impact on the fields of signal and image processing. In this talk we start by presenting this model and its features, and then turn to describe two special cases of it – the convolutional sparse coding (CSC) and its multi-layered version (ML-CSC). Amazingly, as we will carefully show, ML-CSC provides a solid theoretical foundation to … deep-learning.

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Authors:
Michael Elad
Submitted On:
23 January 2018 - 7:06pm
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ICIP_KeyNote_Talk.pdf

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[1] Michael Elad, "Sparse Modeling in Image Processing and Deep Learning (Keynote Talk)", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2259. Accessed: Aug. 21, 2018.
@article{2259-17,
url = {http://sigport.org/2259},
author = {Michael Elad },
publisher = {IEEE SigPort},
title = {Sparse Modeling in Image Processing and Deep Learning (Keynote Talk)},
year = {2017} }
TY - EJOUR
T1 - Sparse Modeling in Image Processing and Deep Learning (Keynote Talk)
AU - Michael Elad
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2259
ER -
Michael Elad. (2017). Sparse Modeling in Image Processing and Deep Learning (Keynote Talk). IEEE SigPort. http://sigport.org/2259
Michael Elad, 2017. Sparse Modeling in Image Processing and Deep Learning (Keynote Talk). Available at: http://sigport.org/2259.
Michael Elad. (2017). "Sparse Modeling in Image Processing and Deep Learning (Keynote Talk)." Web.
1. Michael Elad. Sparse Modeling in Image Processing and Deep Learning (Keynote Talk) [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2259

TOWARDS 3D CONVOLUTIONAL NEURAL NETWORKS WITH MESHES


Voxels are an effective approach to 3D mesh and point cloud classification because they build upon mature Convolutional Neural Network concepts. We show however that their cubic increase in dimensionality is unsuitable for more challenging problems such as object detection in a complex point cloud scene. We observe that 3D meshes are analogous to graph data and can thus be treated with graph signal processing techniques.

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Authors:
Felipe Petroski Such, Shagan Sah, Raymond Ptucha
Submitted On:
19 September 2017 - 11:34am
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ICIPPoster2017MiguelDominguez.pdf

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[1] Felipe Petroski Such, Shagan Sah, Raymond Ptucha, "TOWARDS 3D CONVOLUTIONAL NEURAL NETWORKS WITH MESHES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2234. Accessed: Aug. 21, 2018.
@article{2234-17,
url = {http://sigport.org/2234},
author = {Felipe Petroski Such; Shagan Sah; Raymond Ptucha },
publisher = {IEEE SigPort},
title = {TOWARDS 3D CONVOLUTIONAL NEURAL NETWORKS WITH MESHES},
year = {2017} }
TY - EJOUR
T1 - TOWARDS 3D CONVOLUTIONAL NEURAL NETWORKS WITH MESHES
AU - Felipe Petroski Such; Shagan Sah; Raymond Ptucha
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2234
ER -
Felipe Petroski Such, Shagan Sah, Raymond Ptucha. (2017). TOWARDS 3D CONVOLUTIONAL NEURAL NETWORKS WITH MESHES. IEEE SigPort. http://sigport.org/2234
Felipe Petroski Such, Shagan Sah, Raymond Ptucha, 2017. TOWARDS 3D CONVOLUTIONAL NEURAL NETWORKS WITH MESHES. Available at: http://sigport.org/2234.
Felipe Petroski Such, Shagan Sah, Raymond Ptucha. (2017). "TOWARDS 3D CONVOLUTIONAL NEURAL NETWORKS WITH MESHES." Web.
1. Felipe Petroski Such, Shagan Sah, Raymond Ptucha. TOWARDS 3D CONVOLUTIONAL NEURAL NETWORKS WITH MESHES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2234

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