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Image/Video Processing

WHERE TO PLACE: A REAL-TIME VISUAL SALIENCY BASED LABEL PLACEMENT FOR AUGMENTED REALITY APPLICATIONS

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Authors:
Neel Rakholia, Srinidhi Hegde, Ramya Hebbalaguppe
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8 October 2018 - 3:47pm
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Oral Presentation

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[1] Neel Rakholia, Srinidhi Hegde, Ramya Hebbalaguppe, "WHERE TO PLACE: A REAL-TIME VISUAL SALIENCY BASED LABEL PLACEMENT FOR AUGMENTED REALITY APPLICATIONS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3641. Accessed: Jul. 23, 2019.
@article{3641-18,
url = {http://sigport.org/3641},
author = {Neel Rakholia; Srinidhi Hegde; Ramya Hebbalaguppe },
publisher = {IEEE SigPort},
title = {WHERE TO PLACE: A REAL-TIME VISUAL SALIENCY BASED LABEL PLACEMENT FOR AUGMENTED REALITY APPLICATIONS},
year = {2018} }
TY - EJOUR
T1 - WHERE TO PLACE: A REAL-TIME VISUAL SALIENCY BASED LABEL PLACEMENT FOR AUGMENTED REALITY APPLICATIONS
AU - Neel Rakholia; Srinidhi Hegde; Ramya Hebbalaguppe
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3641
ER -
Neel Rakholia, Srinidhi Hegde, Ramya Hebbalaguppe. (2018). WHERE TO PLACE: A REAL-TIME VISUAL SALIENCY BASED LABEL PLACEMENT FOR AUGMENTED REALITY APPLICATIONS. IEEE SigPort. http://sigport.org/3641
Neel Rakholia, Srinidhi Hegde, Ramya Hebbalaguppe, 2018. WHERE TO PLACE: A REAL-TIME VISUAL SALIENCY BASED LABEL PLACEMENT FOR AUGMENTED REALITY APPLICATIONS. Available at: http://sigport.org/3641.
Neel Rakholia, Srinidhi Hegde, Ramya Hebbalaguppe. (2018). "WHERE TO PLACE: A REAL-TIME VISUAL SALIENCY BASED LABEL PLACEMENT FOR AUGMENTED REALITY APPLICATIONS." Web.
1. Neel Rakholia, Srinidhi Hegde, Ramya Hebbalaguppe. WHERE TO PLACE: A REAL-TIME VISUAL SALIENCY BASED LABEL PLACEMENT FOR AUGMENTED REALITY APPLICATIONS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3641

R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION


Point cloud are precise digital record of an objects in space. It starts to getting more attention due to the additional information it provides compared to 2D images. In this paper, we propose a new deep learning architecture called R-CovNets, designed for 3D object recognition. Unlike to previous approaches that usually sample or convert point cloud into three-dimensional grids, R-CovNets does not reckon on any preprocessing. Our architecture is specially designed for cloud point, permutation invariant and can take as input, a data of any size.

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Authors:
Danielle Tchuinkou Kwadj and Christophe Bobda
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8 October 2018 - 2:07pm
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[1] Danielle Tchuinkou Kwadj and Christophe Bobda, "R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3638. Accessed: Jul. 23, 2019.
@article{3638-18,
url = {http://sigport.org/3638},
author = {Danielle Tchuinkou Kwadj and Christophe Bobda },
publisher = {IEEE SigPort},
title = {R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION},
year = {2018} }
TY - EJOUR
T1 - R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION
AU - Danielle Tchuinkou Kwadj and Christophe Bobda
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3638
ER -
Danielle Tchuinkou Kwadj and Christophe Bobda. (2018). R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION. IEEE SigPort. http://sigport.org/3638
Danielle Tchuinkou Kwadj and Christophe Bobda, 2018. R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION. Available at: http://sigport.org/3638.
Danielle Tchuinkou Kwadj and Christophe Bobda. (2018). "R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION." Web.
1. Danielle Tchuinkou Kwadj and Christophe Bobda. R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3638

NON-LOCAL KALMAN: A RECURSIVE VIDEO DENOISING ALGORITHM

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Authors:
Thibaud Ehret, Jean-Michel Morel, Pablo Arias
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8 October 2018 - 8:28am
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icip-nlk.pdf

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[1] Thibaud Ehret, Jean-Michel Morel, Pablo Arias, "NON-LOCAL KALMAN: A RECURSIVE VIDEO DENOISING ALGORITHM", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3630. Accessed: Jul. 23, 2019.
@article{3630-18,
url = {http://sigport.org/3630},
author = {Thibaud Ehret; Jean-Michel Morel; Pablo Arias },
publisher = {IEEE SigPort},
title = {NON-LOCAL KALMAN: A RECURSIVE VIDEO DENOISING ALGORITHM},
year = {2018} }
TY - EJOUR
T1 - NON-LOCAL KALMAN: A RECURSIVE VIDEO DENOISING ALGORITHM
AU - Thibaud Ehret; Jean-Michel Morel; Pablo Arias
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3630
ER -
Thibaud Ehret, Jean-Michel Morel, Pablo Arias. (2018). NON-LOCAL KALMAN: A RECURSIVE VIDEO DENOISING ALGORITHM. IEEE SigPort. http://sigport.org/3630
Thibaud Ehret, Jean-Michel Morel, Pablo Arias, 2018. NON-LOCAL KALMAN: A RECURSIVE VIDEO DENOISING ALGORITHM. Available at: http://sigport.org/3630.
Thibaud Ehret, Jean-Michel Morel, Pablo Arias. (2018). "NON-LOCAL KALMAN: A RECURSIVE VIDEO DENOISING ALGORITHM." Web.
1. Thibaud Ehret, Jean-Michel Morel, Pablo Arias. NON-LOCAL KALMAN: A RECURSIVE VIDEO DENOISING ALGORITHM [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3630

REDUCING ANOMALY DETECTION IN IMAGES TO DETECTION IN NOISE

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Authors:
Axel Davy, Thibaud Ehret, Jean-Michel Morel, Mauricio Delbracio
Submitted On:
8 October 2018 - 8:26am
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icip-det.pdf

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[1] Axel Davy, Thibaud Ehret, Jean-Michel Morel, Mauricio Delbracio, "REDUCING ANOMALY DETECTION IN IMAGES TO DETECTION IN NOISE", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3629. Accessed: Jul. 23, 2019.
@article{3629-18,
url = {http://sigport.org/3629},
author = {Axel Davy; Thibaud Ehret; Jean-Michel Morel; Mauricio Delbracio },
publisher = {IEEE SigPort},
title = {REDUCING ANOMALY DETECTION IN IMAGES TO DETECTION IN NOISE},
year = {2018} }
TY - EJOUR
T1 - REDUCING ANOMALY DETECTION IN IMAGES TO DETECTION IN NOISE
AU - Axel Davy; Thibaud Ehret; Jean-Michel Morel; Mauricio Delbracio
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3629
ER -
Axel Davy, Thibaud Ehret, Jean-Michel Morel, Mauricio Delbracio. (2018). REDUCING ANOMALY DETECTION IN IMAGES TO DETECTION IN NOISE. IEEE SigPort. http://sigport.org/3629
Axel Davy, Thibaud Ehret, Jean-Michel Morel, Mauricio Delbracio, 2018. REDUCING ANOMALY DETECTION IN IMAGES TO DETECTION IN NOISE. Available at: http://sigport.org/3629.
Axel Davy, Thibaud Ehret, Jean-Michel Morel, Mauricio Delbracio. (2018). "REDUCING ANOMALY DETECTION IN IMAGES TO DETECTION IN NOISE." Web.
1. Axel Davy, Thibaud Ehret, Jean-Michel Morel, Mauricio Delbracio. REDUCING ANOMALY DETECTION IN IMAGES TO DETECTION IN NOISE [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3629

DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION

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8 October 2018 - 5:46am
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Poster for paper 2904

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[1] , "DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION ", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3624. Accessed: Jul. 23, 2019.
@article{3624-18,
url = {http://sigport.org/3624},
author = { },
publisher = {IEEE SigPort},
title = {DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION },
year = {2018} }
TY - EJOUR
T1 - DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3624
ER -
. (2018). DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION . IEEE SigPort. http://sigport.org/3624
, 2018. DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION . Available at: http://sigport.org/3624.
. (2018). "DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION ." Web.
1. . DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3624

DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION

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Submitted On:
8 October 2018 - 5:46am
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Poster for paper 2904

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[1] , "DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION ", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3623. Accessed: Jul. 23, 2019.
@article{3623-18,
url = {http://sigport.org/3623},
author = { },
publisher = {IEEE SigPort},
title = {DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION },
year = {2018} }
TY - EJOUR
T1 - DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3623
ER -
. (2018). DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION . IEEE SigPort. http://sigport.org/3623
, 2018. DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION . Available at: http://sigport.org/3623.
. (2018). "DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION ." Web.
1. . DISCOVER THE EFFECTIVE STRATEGY FOR FACE RECOGNITION MODEL COMPRESSION BY IMPROVED KNOWLEDGE DISTILLATION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3623

SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630

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Authors:
Nicole Schmidt, Arne Schumann, Jürgen Beyerer
Submitted On:
8 October 2018 - 3:52am
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[1] Nicole Schmidt, Arne Schumann, Jürgen Beyerer, "SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3621. Accessed: Jul. 23, 2019.
@article{3621-18,
url = {http://sigport.org/3621},
author = {Nicole Schmidt; Arne Schumann; Jürgen Beyerer },
publisher = {IEEE SigPort},
title = {SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630},
year = {2018} }
TY - EJOUR
T1 - SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630
AU - Nicole Schmidt; Arne Schumann; Jürgen Beyerer
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3621
ER -
Nicole Schmidt, Arne Schumann, Jürgen Beyerer. (2018). SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630. IEEE SigPort. http://sigport.org/3621
Nicole Schmidt, Arne Schumann, Jürgen Beyerer, 2018. SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630. Available at: http://sigport.org/3621.
Nicole Schmidt, Arne Schumann, Jürgen Beyerer. (2018). "SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630." Web.
1. Nicole Schmidt, Arne Schumann, Jürgen Beyerer. SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630 [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3621

SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630

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Authors:
Nicole Schmidt, Arne Schumann, Jürgen Beyerer
Submitted On:
8 October 2018 - 3:52am
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ICIP2018_paper_1630.pdf

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[1] Nicole Schmidt, Arne Schumann, Jürgen Beyerer, "SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3620. Accessed: Jul. 23, 2019.
@article{3620-18,
url = {http://sigport.org/3620},
author = {Nicole Schmidt; Arne Schumann; Jürgen Beyerer },
publisher = {IEEE SigPort},
title = {SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630},
year = {2018} }
TY - EJOUR
T1 - SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630
AU - Nicole Schmidt; Arne Schumann; Jürgen Beyerer
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3620
ER -
Nicole Schmidt, Arne Schumann, Jürgen Beyerer. (2018). SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630. IEEE SigPort. http://sigport.org/3620
Nicole Schmidt, Arne Schumann, Jürgen Beyerer, 2018. SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630. Available at: http://sigport.org/3620.
Nicole Schmidt, Arne Schumann, Jürgen Beyerer. (2018). "SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630." Web.
1. Nicole Schmidt, Arne Schumann, Jürgen Beyerer. SIGPORT FOR THE 2018 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) for paper 1630 [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3620

CONDITIONAL DISTRIBUTION LEARNING WITH NEURAL NETWORKS AND ITS APPLICATION TO UNIVERSAL IMAGE DENOISING


A simple and scalable denoising algorithm is proposed that can be applied to a wide range of source and noise models. At the core of the proposed CUDE algorithm is symbol-by-symbol universal denoising used by the celebrated DUDE algorithm, whereby the optimal estimate of the source from an unknown distribution is computed by inverting the empirical distribution of the noisy observation sequence by a deep neural network, which naturally and implicitly aggregates multiple contexts of similar characteristics and estimates the conditional distribution more accurately.

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Authors:
Jongha Jon Ryu, Young-Han Kim
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8 October 2018 - 3:38am
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[1] Jongha Jon Ryu, Young-Han Kim, "CONDITIONAL DISTRIBUTION LEARNING WITH NEURAL NETWORKS AND ITS APPLICATION TO UNIVERSAL IMAGE DENOISING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3616. Accessed: Jul. 23, 2019.
@article{3616-18,
url = {http://sigport.org/3616},
author = {Jongha Jon Ryu; Young-Han Kim },
publisher = {IEEE SigPort},
title = {CONDITIONAL DISTRIBUTION LEARNING WITH NEURAL NETWORKS AND ITS APPLICATION TO UNIVERSAL IMAGE DENOISING},
year = {2018} }
TY - EJOUR
T1 - CONDITIONAL DISTRIBUTION LEARNING WITH NEURAL NETWORKS AND ITS APPLICATION TO UNIVERSAL IMAGE DENOISING
AU - Jongha Jon Ryu; Young-Han Kim
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3616
ER -
Jongha Jon Ryu, Young-Han Kim. (2018). CONDITIONAL DISTRIBUTION LEARNING WITH NEURAL NETWORKS AND ITS APPLICATION TO UNIVERSAL IMAGE DENOISING. IEEE SigPort. http://sigport.org/3616
Jongha Jon Ryu, Young-Han Kim, 2018. CONDITIONAL DISTRIBUTION LEARNING WITH NEURAL NETWORKS AND ITS APPLICATION TO UNIVERSAL IMAGE DENOISING. Available at: http://sigport.org/3616.
Jongha Jon Ryu, Young-Han Kim. (2018). "CONDITIONAL DISTRIBUTION LEARNING WITH NEURAL NETWORKS AND ITS APPLICATION TO UNIVERSAL IMAGE DENOISING." Web.
1. Jongha Jon Ryu, Young-Han Kim. CONDITIONAL DISTRIBUTION LEARNING WITH NEURAL NETWORKS AND ITS APPLICATION TO UNIVERSAL IMAGE DENOISING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3616

Normal Similarity Network for Generative Modelling

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Authors:
Jay Nandy, Wynne Hsu, Lee Mong Li
Submitted On:
8 October 2018 - 3:12am
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icip (2).pdf

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[1] Jay Nandy, Wynne Hsu, Lee Mong Li, "Normal Similarity Network for Generative Modelling", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3614. Accessed: Jul. 23, 2019.
@article{3614-18,
url = {http://sigport.org/3614},
author = {Jay Nandy; Wynne Hsu; Lee Mong Li },
publisher = {IEEE SigPort},
title = {Normal Similarity Network for Generative Modelling},
year = {2018} }
TY - EJOUR
T1 - Normal Similarity Network for Generative Modelling
AU - Jay Nandy; Wynne Hsu; Lee Mong Li
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3614
ER -
Jay Nandy, Wynne Hsu, Lee Mong Li. (2018). Normal Similarity Network for Generative Modelling. IEEE SigPort. http://sigport.org/3614
Jay Nandy, Wynne Hsu, Lee Mong Li, 2018. Normal Similarity Network for Generative Modelling. Available at: http://sigport.org/3614.
Jay Nandy, Wynne Hsu, Lee Mong Li. (2018). "Normal Similarity Network for Generative Modelling." Web.
1. Jay Nandy, Wynne Hsu, Lee Mong Li. Normal Similarity Network for Generative Modelling [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3614

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