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ICASSP 2019

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

Joint Codebook Design for Multi-Cell NOMA


For spreading-based multiple access, whether orthogonal (OMA) or non-orthogonal (NOMA), the spreading sequences (signatures) are selected from a predefined codebook. When operating in a cellular system, intercell interference will be inherently present between close base stations that share the same resources. If the codebook is reused across the different cells, then intercell interference can cause a full collision of the interfering users in the code-domain, thus deteriorating their performance, especially those at the cell-edge.

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Authors:
Bashar Tahir, Stefan Schwarz, Markus Rupp
Submitted On:
7 May 2019 - 1:29pm
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JointCodebookDesignNOMA_Poster.pdf

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[1] Bashar Tahir, Stefan Schwarz, Markus Rupp, "Joint Codebook Design for Multi-Cell NOMA", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3928. Accessed: Jan. 19, 2020.
@article{3928-19,
url = {http://sigport.org/3928},
author = {Bashar Tahir; Stefan Schwarz; Markus Rupp },
publisher = {IEEE SigPort},
title = {Joint Codebook Design for Multi-Cell NOMA},
year = {2019} }
TY - EJOUR
T1 - Joint Codebook Design for Multi-Cell NOMA
AU - Bashar Tahir; Stefan Schwarz; Markus Rupp
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3928
ER -
Bashar Tahir, Stefan Schwarz, Markus Rupp. (2019). Joint Codebook Design for Multi-Cell NOMA. IEEE SigPort. http://sigport.org/3928
Bashar Tahir, Stefan Schwarz, Markus Rupp, 2019. Joint Codebook Design for Multi-Cell NOMA. Available at: http://sigport.org/3928.
Bashar Tahir, Stefan Schwarz, Markus Rupp. (2019). "Joint Codebook Design for Multi-Cell NOMA." Web.
1. Bashar Tahir, Stefan Schwarz, Markus Rupp. Joint Codebook Design for Multi-Cell NOMA [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3928

PhoneSpoof: A new dataset for spoofing attack detection in telephone channel


The results of spoofing detection systems proposed during ASVspoof Challenges 2015 and 2017 confirmed the perspective in detection of unforseen spoofing trials in microphone channel. However, telephone channel presents much more challenging conditions for spoofing detection, due to limited bandwidth, various coding standards and channel effects. Research on the topic has thus far only made use of program codecs and other telephone channel emulations. Such emulations does not quite match the real telephone spoofing attacks.

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Authors:
Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico
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7 May 2019 - 1:13pm
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ICASSP-2019.pdf

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[1] Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico, "PhoneSpoof: A new dataset for spoofing attack detection in telephone channel", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3927. Accessed: Jan. 19, 2020.
@article{3927-19,
url = {http://sigport.org/3927},
author = {Galina Lavrentyeva; Sergey Novoselov; Marina Volkova; Yuri Matveev; Maria De Marsico },
publisher = {IEEE SigPort},
title = {PhoneSpoof: A new dataset for spoofing attack detection in telephone channel},
year = {2019} }
TY - EJOUR
T1 - PhoneSpoof: A new dataset for spoofing attack detection in telephone channel
AU - Galina Lavrentyeva; Sergey Novoselov; Marina Volkova; Yuri Matveev; Maria De Marsico
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3927
ER -
Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico. (2019). PhoneSpoof: A new dataset for spoofing attack detection in telephone channel. IEEE SigPort. http://sigport.org/3927
Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico, 2019. PhoneSpoof: A new dataset for spoofing attack detection in telephone channel. Available at: http://sigport.org/3927.
Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico. (2019). "PhoneSpoof: A new dataset for spoofing attack detection in telephone channel." Web.
1. Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico. PhoneSpoof: A new dataset for spoofing attack detection in telephone channel [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3927

On the Usefulness of Statistical Normalisation of Bottleneck Features for Speech Recognition


DNNs play a major role in the state-of-the-art ASR systems. They can be used for extracting features and building probabilistic models for acoustic and language modelling. Despite their huge practical success, the level of theoretical understanding has remained shallow. This paper investigates DNNs from a statistical standpoint. In particular, the effect of activation functions on the distribution of the pre-activations and activations is investigated and discussed from both analytic and empirical viewpoints.

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Authors:
Erfan Loweimi, Peter Bell, Steve Renals
Submitted On:
7 May 2019 - 1:08pm
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[1] Erfan Loweimi, Peter Bell, Steve Renals, "On the Usefulness of Statistical Normalisation of Bottleneck Features for Speech Recognition", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3926. Accessed: Jan. 19, 2020.
@article{3926-19,
url = {http://sigport.org/3926},
author = {Erfan Loweimi; Peter Bell; Steve Renals },
publisher = {IEEE SigPort},
title = {On the Usefulness of Statistical Normalisation of Bottleneck Features for Speech Recognition},
year = {2019} }
TY - EJOUR
T1 - On the Usefulness of Statistical Normalisation of Bottleneck Features for Speech Recognition
AU - Erfan Loweimi; Peter Bell; Steve Renals
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3926
ER -
Erfan Loweimi, Peter Bell, Steve Renals. (2019). On the Usefulness of Statistical Normalisation of Bottleneck Features for Speech Recognition. IEEE SigPort. http://sigport.org/3926
Erfan Loweimi, Peter Bell, Steve Renals, 2019. On the Usefulness of Statistical Normalisation of Bottleneck Features for Speech Recognition. Available at: http://sigport.org/3926.
Erfan Loweimi, Peter Bell, Steve Renals. (2019). "On the Usefulness of Statistical Normalisation of Bottleneck Features for Speech Recognition." Web.
1. Erfan Loweimi, Peter Bell, Steve Renals. On the Usefulness of Statistical Normalisation of Bottleneck Features for Speech Recognition [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3926

OBJECTIVE COMPARISON OF SPEECH ENHANCEMENT ALGORITHMS WITH HEARING LOSS SIMULATION


Many speech enhancement algorithms have been proposed over the years and it has been shown that deep neural networks can lead to significant improvements. These algorithms, however, have not been validated for hearing-impaired listeners. Additionally, these algorithms are often evaluated under a limited range of signal-to-noise ratios (SNR). Here, we construct a diverse speech dataset with a broad range of SNRs and noises.

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Authors:
Zhuohuang Zhang, Yi Shen, Donald S. Williamson
Submitted On:
7 May 2019 - 1:03pm
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ICASSP 2019 Zhang.pdf

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[1] Zhuohuang Zhang, Yi Shen, Donald S. Williamson, "OBJECTIVE COMPARISON OF SPEECH ENHANCEMENT ALGORITHMS WITH HEARING LOSS SIMULATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3925. Accessed: Jan. 19, 2020.
@article{3925-19,
url = {http://sigport.org/3925},
author = {Zhuohuang Zhang; Yi Shen; Donald S. Williamson },
publisher = {IEEE SigPort},
title = {OBJECTIVE COMPARISON OF SPEECH ENHANCEMENT ALGORITHMS WITH HEARING LOSS SIMULATION},
year = {2019} }
TY - EJOUR
T1 - OBJECTIVE COMPARISON OF SPEECH ENHANCEMENT ALGORITHMS WITH HEARING LOSS SIMULATION
AU - Zhuohuang Zhang; Yi Shen; Donald S. Williamson
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3925
ER -
Zhuohuang Zhang, Yi Shen, Donald S. Williamson. (2019). OBJECTIVE COMPARISON OF SPEECH ENHANCEMENT ALGORITHMS WITH HEARING LOSS SIMULATION. IEEE SigPort. http://sigport.org/3925
Zhuohuang Zhang, Yi Shen, Donald S. Williamson, 2019. OBJECTIVE COMPARISON OF SPEECH ENHANCEMENT ALGORITHMS WITH HEARING LOSS SIMULATION. Available at: http://sigport.org/3925.
Zhuohuang Zhang, Yi Shen, Donald S. Williamson. (2019). "OBJECTIVE COMPARISON OF SPEECH ENHANCEMENT ALGORITHMS WITH HEARING LOSS SIMULATION." Web.
1. Zhuohuang Zhang, Yi Shen, Donald S. Williamson. OBJECTIVE COMPARISON OF SPEECH ENHANCEMENT ALGORITHMS WITH HEARING LOSS SIMULATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3925

Occupancy pattern recognition with infrared array sensors: A Bayesian approach to multi-body tracking

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Authors:
Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush, Alberto Minora, Leonardo Costa
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7 May 2019 - 1:01pm
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[1] Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush, Alberto Minora, Leonardo Costa, "Occupancy pattern recognition with infrared array sensors: A Bayesian approach to multi-body tracking", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3924. Accessed: Jan. 19, 2020.
@article{3924-19,
url = {http://sigport.org/3924},
author = {Stefano Savazzi; Vittorio Rampa; Sanaz Kianoush; Alberto Minora; Leonardo Costa },
publisher = {IEEE SigPort},
title = {Occupancy pattern recognition with infrared array sensors: A Bayesian approach to multi-body tracking},
year = {2019} }
TY - EJOUR
T1 - Occupancy pattern recognition with infrared array sensors: A Bayesian approach to multi-body tracking
AU - Stefano Savazzi; Vittorio Rampa; Sanaz Kianoush; Alberto Minora; Leonardo Costa
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3924
ER -
Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush, Alberto Minora, Leonardo Costa. (2019). Occupancy pattern recognition with infrared array sensors: A Bayesian approach to multi-body tracking. IEEE SigPort. http://sigport.org/3924
Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush, Alberto Minora, Leonardo Costa, 2019. Occupancy pattern recognition with infrared array sensors: A Bayesian approach to multi-body tracking. Available at: http://sigport.org/3924.
Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush, Alberto Minora, Leonardo Costa. (2019). "Occupancy pattern recognition with infrared array sensors: A Bayesian approach to multi-body tracking." Web.
1. Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush, Alberto Minora, Leonardo Costa. Occupancy pattern recognition with infrared array sensors: A Bayesian approach to multi-body tracking [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3924

SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING


In this paper, we address the fundamental problem of Sparse
Bayesian Learning (SBL), where the received signal is a high-order
tensor. We furthermore consider the problem of dictionary learning
(DL), where the tensor observations are assumed to be generated
from a Kronecker structured (KS) dictionary matrix multiplied by
the sparse coefficients. Exploiting the tensorial structure results in
a reduction in the number of degrees of freedom in the learning
problem, since the dimensions of each of the factor matrices are significantly

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7 May 2019 - 12:58pm
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[1] , "SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3923. Accessed: Jan. 19, 2020.
@article{3923-19,
url = {http://sigport.org/3923},
author = { },
publisher = {IEEE SigPort},
title = {SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING},
year = {2019} }
TY - EJOUR
T1 - SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3923
ER -
. (2019). SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING. IEEE SigPort. http://sigport.org/3923
, 2019. SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING. Available at: http://sigport.org/3923.
. (2019). "SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING." Web.
1. . SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3923

PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE


The problem of higher order sound field capture with spherical microphone arrays is considered. While A-format cardioid designs are commonplace for first order capture, interest remains in the increased spatial resolution delivered by higher order arrays. Spherical arrays typically use omnidirectional microphones mounted on a rigid baffle, from which higher order spatial components are estimated by accounting for radial mode strength.

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7 May 2019 - 12:54pm
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Dual Open Sphere Microphone Arrays.pdf

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[1] , "PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3922. Accessed: Jan. 19, 2020.
@article{3922-19,
url = {http://sigport.org/3922},
author = { },
publisher = {IEEE SigPort},
title = {PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE},
year = {2019} }
TY - EJOUR
T1 - PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3922
ER -
. (2019). PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE. IEEE SigPort. http://sigport.org/3922
, 2019. PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE. Available at: http://sigport.org/3922.
. (2019). "PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE." Web.
1. . PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3922

A Novel Approximate Lloyd-Max Quantizer and Its Analysis


Several distributed real-time signal sensing/monitoring systems require quantization for efficient signal representation. These distributed sensors often have computational and energy limitations. Motivated by this concern, we propose a novel quantization scheme called Approximate Lloyd-Max (ALM) that is nearly-optimal. Assuming a continuous and finite support probability distribution of the source, we show that our ALM quantizer converges to the classical Lloyd-Max quantizer with increasing bitrate.

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Authors:
Vijay Anavangot, Animesh Kumar
Submitted On:
8 May 2019 - 1:25am
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Poster for ICASSP 2019

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[1] Vijay Anavangot, Animesh Kumar, "A Novel Approximate Lloyd-Max Quantizer and Its Analysis", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3921. Accessed: Jan. 19, 2020.
@article{3921-19,
url = {http://sigport.org/3921},
author = {Vijay Anavangot; Animesh Kumar },
publisher = {IEEE SigPort},
title = {A Novel Approximate Lloyd-Max Quantizer and Its Analysis},
year = {2019} }
TY - EJOUR
T1 - A Novel Approximate Lloyd-Max Quantizer and Its Analysis
AU - Vijay Anavangot; Animesh Kumar
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3921
ER -
Vijay Anavangot, Animesh Kumar. (2019). A Novel Approximate Lloyd-Max Quantizer and Its Analysis. IEEE SigPort. http://sigport.org/3921
Vijay Anavangot, Animesh Kumar, 2019. A Novel Approximate Lloyd-Max Quantizer and Its Analysis. Available at: http://sigport.org/3921.
Vijay Anavangot, Animesh Kumar. (2019). "A Novel Approximate Lloyd-Max Quantizer and Its Analysis." Web.
1. Vijay Anavangot, Animesh Kumar. A Novel Approximate Lloyd-Max Quantizer and Its Analysis [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3921

Reconfigurable Multitask Audio Dynamics Processing Scheme


Automatic speech recognition (ASR), audio quality, and loudness are key performance indicators (KPIs) in smart speakers. To improve all these KPIs, audio dynamics processing is a crucial component in related systems. Unfortunately, single-band and existing multiband dynamics processing (MBDP) schemes fail to maximize bass and loudness but even produce unwanted peaks, distortions, and nonlinear echo so that an optimized ASR performance cannot be achieved. It has been a goal in both industry and academia to find a better audio dynamics processing for mitigating these problems.

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Authors:
Jun Yang, Amit S. Chhetri, Carlo Murgia, Philip Hilmes
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7 May 2019 - 4:47pm
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[1] Jun Yang, Amit S. Chhetri, Carlo Murgia, Philip Hilmes, "Reconfigurable Multitask Audio Dynamics Processing Scheme", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3920. Accessed: Jan. 19, 2020.
@article{3920-19,
url = {http://sigport.org/3920},
author = {Jun Yang; Amit S. Chhetri; Carlo Murgia; Philip Hilmes },
publisher = {IEEE SigPort},
title = {Reconfigurable Multitask Audio Dynamics Processing Scheme},
year = {2019} }
TY - EJOUR
T1 - Reconfigurable Multitask Audio Dynamics Processing Scheme
AU - Jun Yang; Amit S. Chhetri; Carlo Murgia; Philip Hilmes
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3920
ER -
Jun Yang, Amit S. Chhetri, Carlo Murgia, Philip Hilmes. (2019). Reconfigurable Multitask Audio Dynamics Processing Scheme. IEEE SigPort. http://sigport.org/3920
Jun Yang, Amit S. Chhetri, Carlo Murgia, Philip Hilmes, 2019. Reconfigurable Multitask Audio Dynamics Processing Scheme. Available at: http://sigport.org/3920.
Jun Yang, Amit S. Chhetri, Carlo Murgia, Philip Hilmes. (2019). "Reconfigurable Multitask Audio Dynamics Processing Scheme." Web.
1. Jun Yang, Amit S. Chhetri, Carlo Murgia, Philip Hilmes. Reconfigurable Multitask Audio Dynamics Processing Scheme [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3920

DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS


In this paper, we propose a statistical framework to prune feature maps in 1-D deep convolutional networks. SoundNet is a pre-trained deep convolutional network that accepts raw audio samples as input. The feature maps generated at various layers of SoundNet have redundancy, which can be identified by statistical analysis. These redundant feature maps can be pruned from the network with a very minor reduction in the capability of the network.

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Authors:
Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar
Submitted On:
7 May 2019 - 1:19am
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ICASSP_arsh.pdf

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[1] Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar , "DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3919. Accessed: Jan. 19, 2020.
@article{3919-19,
url = {http://sigport.org/3919},
author = { Arshdeep Singh ; Padmanabhan Rajan ; Arnav Bhavsar },
publisher = {IEEE SigPort},
title = {DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS},
year = {2019} }
TY - EJOUR
T1 - DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS
AU - Arshdeep Singh ; Padmanabhan Rajan ; Arnav Bhavsar
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3919
ER -
Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar . (2019). DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS. IEEE SigPort. http://sigport.org/3919
Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar , 2019. DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS. Available at: http://sigport.org/3919.
Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar . (2019). "DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS." Web.
1. Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar . DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3919

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