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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

Low-latency deep clustering for speech separation


This paper proposes a low algorithmic latency adaptation of the deep clustering approach to speaker-independent speech separation. It consists of three parts: a) the usage of long-short-term-memory (LSTM) networks instead of their bidirectional variant used in the original work, b) using a short synthesis window (here 8 ms) required for low-latency operation, and, c) using a buffer in the beginning of audio mixture to estimate cluster centres corresponding to constituent speakers which are then utilized to separate speakers within the rest of the signal.

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Authors:
Shanshan Wang, Gaurav Naithani, Tuomas Virtanen
Submitted On:
7 May 2019 - 1:32pm
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[1] Shanshan Wang, Gaurav Naithani, Tuomas Virtanen, "Low-latency deep clustering for speech separation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3908. Accessed: Jul. 08, 2020.
@article{3908-19,
url = {http://sigport.org/3908},
author = {Shanshan Wang; Gaurav Naithani; Tuomas Virtanen },
publisher = {IEEE SigPort},
title = {Low-latency deep clustering for speech separation},
year = {2019} }
TY - EJOUR
T1 - Low-latency deep clustering for speech separation
AU - Shanshan Wang; Gaurav Naithani; Tuomas Virtanen
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3908
ER -
Shanshan Wang, Gaurav Naithani, Tuomas Virtanen. (2019). Low-latency deep clustering for speech separation. IEEE SigPort. http://sigport.org/3908
Shanshan Wang, Gaurav Naithani, Tuomas Virtanen, 2019. Low-latency deep clustering for speech separation. Available at: http://sigport.org/3908.
Shanshan Wang, Gaurav Naithani, Tuomas Virtanen. (2019). "Low-latency deep clustering for speech separation." Web.
1. Shanshan Wang, Gaurav Naithani, Tuomas Virtanen. Low-latency deep clustering for speech separation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3908

Representation learning using convolution neural network for acoustic-to-articulatory inversion

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Authors:
Aravind Illa, Prasanta Kumar Ghosh
Submitted On:
4 May 2019 - 8:15am
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E2E_AAI_ICASSP_19.pdf

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[1] Aravind Illa, Prasanta Kumar Ghosh, "Representation learning using convolution neural network for acoustic-to-articulatory inversion", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3907. Accessed: Jul. 08, 2020.
@article{3907-19,
url = {http://sigport.org/3907},
author = {Aravind Illa; Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = {Representation learning using convolution neural network for acoustic-to-articulatory inversion},
year = {2019} }
TY - EJOUR
T1 - Representation learning using convolution neural network for acoustic-to-articulatory inversion
AU - Aravind Illa; Prasanta Kumar Ghosh
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3907
ER -
Aravind Illa, Prasanta Kumar Ghosh. (2019). Representation learning using convolution neural network for acoustic-to-articulatory inversion. IEEE SigPort. http://sigport.org/3907
Aravind Illa, Prasanta Kumar Ghosh, 2019. Representation learning using convolution neural network for acoustic-to-articulatory inversion. Available at: http://sigport.org/3907.
Aravind Illa, Prasanta Kumar Ghosh. (2019). "Representation learning using convolution neural network for acoustic-to-articulatory inversion." Web.
1. Aravind Illa, Prasanta Kumar Ghosh. Representation learning using convolution neural network for acoustic-to-articulatory inversion [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3907

A Low-latency Sparse-winograd Accelerator for Convolutional Neural Networks

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Authors:
Haonan Wang, Wenjian Liu, Tianyi Xu, Jun Lin, Zhongfeng Wang
Submitted On:
4 May 2019 - 1:19am
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[1] Haonan Wang, Wenjian Liu, Tianyi Xu, Jun Lin, Zhongfeng Wang, "A Low-latency Sparse-winograd Accelerator for Convolutional Neural Networks", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3906. Accessed: Jul. 08, 2020.
@article{3906-19,
url = {http://sigport.org/3906},
author = {Haonan Wang; Wenjian Liu; Tianyi Xu; Jun Lin; Zhongfeng Wang },
publisher = {IEEE SigPort},
title = {A Low-latency Sparse-winograd Accelerator for Convolutional Neural Networks},
year = {2019} }
TY - EJOUR
T1 - A Low-latency Sparse-winograd Accelerator for Convolutional Neural Networks
AU - Haonan Wang; Wenjian Liu; Tianyi Xu; Jun Lin; Zhongfeng Wang
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3906
ER -
Haonan Wang, Wenjian Liu, Tianyi Xu, Jun Lin, Zhongfeng Wang. (2019). A Low-latency Sparse-winograd Accelerator for Convolutional Neural Networks. IEEE SigPort. http://sigport.org/3906
Haonan Wang, Wenjian Liu, Tianyi Xu, Jun Lin, Zhongfeng Wang, 2019. A Low-latency Sparse-winograd Accelerator for Convolutional Neural Networks. Available at: http://sigport.org/3906.
Haonan Wang, Wenjian Liu, Tianyi Xu, Jun Lin, Zhongfeng Wang. (2019). "A Low-latency Sparse-winograd Accelerator for Convolutional Neural Networks." Web.
1. Haonan Wang, Wenjian Liu, Tianyi Xu, Jun Lin, Zhongfeng Wang. A Low-latency Sparse-winograd Accelerator for Convolutional Neural Networks [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3906

DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM


This work considers a design of network in which multiple transmission points (TPs) cooperatively serve users by jointly precoding shared data. Considered problem formulation jointly designs the beamformers and performs TP-UE link selection, which aims in improving overall system rate. Proposed distributed Augmented ADMM algorithm features parallelization among TPs, which has practical importance for computational load distribution and reducing signaling overhead in backhaul.

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Authors:
Submitted On:
3 May 2019 - 3:37pm
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[1] , "DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3905. Accessed: Jul. 08, 2020.
@article{3905-19,
url = {http://sigport.org/3905},
author = { },
publisher = {IEEE SigPort},
title = {DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM},
year = {2019} }
TY - EJOUR
T1 - DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3905
ER -
. (2019). DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM. IEEE SigPort. http://sigport.org/3905
, 2019. DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM. Available at: http://sigport.org/3905.
. (2019). "DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM." Web.
1. . DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3905

DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM


This work considers a design of network in which multiple transmission points (TPs) cooperatively serve users by jointly precoding shared data. Considered problem formulation jointly designs the beamformers and performs TP-UE link selection, which aims in improving overall system rate. Proposed distributed Augmented ADMM algorithm features parallelization among TPs, which has practical importance for computational load distribution and reducing signaling overhead in backhaul. This approach is different from others

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Authors:
Submitted On:
3 May 2019 - 3:36pm
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[1] , "DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3904. Accessed: Jul. 08, 2020.
@article{3904-19,
url = {http://sigport.org/3904},
author = { },
publisher = {IEEE SigPort},
title = {DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM},
year = {2019} }
TY - EJOUR
T1 - DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3904
ER -
. (2019). DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM. IEEE SigPort. http://sigport.org/3904
, 2019. DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM. Available at: http://sigport.org/3904.
. (2019). "DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM." Web.
1. . DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3904

Nonlinear State Estimation using Particle Filters on the Stiefel Manifold


Many problems in statistical signal processing involve tracking the state of a dynamic system that evolves on a Stiefel manifold. To this aim, we introduce in this paper a novel particle filter algorithm that approximates the optimal importance function on the Stiefel manifold and is capable of handling nonlinear observation functions. To sample from the required importance function, we develop adaptations of previous MCMC algorithms.

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Authors:
Claudio Bordin Jr., Marcelo G. S. Bruno
Submitted On:
8 May 2019 - 4:39pm
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[1] Claudio Bordin Jr., Marcelo G. S. Bruno, "Nonlinear State Estimation using Particle Filters on the Stiefel Manifold", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3903. Accessed: Jul. 08, 2020.
@article{3903-19,
url = {http://sigport.org/3903},
author = {Claudio Bordin Jr.; Marcelo G. S. Bruno },
publisher = {IEEE SigPort},
title = {Nonlinear State Estimation using Particle Filters on the Stiefel Manifold},
year = {2019} }
TY - EJOUR
T1 - Nonlinear State Estimation using Particle Filters on the Stiefel Manifold
AU - Claudio Bordin Jr.; Marcelo G. S. Bruno
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3903
ER -
Claudio Bordin Jr., Marcelo G. S. Bruno. (2019). Nonlinear State Estimation using Particle Filters on the Stiefel Manifold. IEEE SigPort. http://sigport.org/3903
Claudio Bordin Jr., Marcelo G. S. Bruno, 2019. Nonlinear State Estimation using Particle Filters on the Stiefel Manifold. Available at: http://sigport.org/3903.
Claudio Bordin Jr., Marcelo G. S. Bruno. (2019). "Nonlinear State Estimation using Particle Filters on the Stiefel Manifold." Web.
1. Claudio Bordin Jr., Marcelo G. S. Bruno. Nonlinear State Estimation using Particle Filters on the Stiefel Manifold [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3903

SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION


Research about brain activities involving spoken word production is considerably underdeveloped because of the undiscovered characteristics of speech artifacts, which contaminate electroencephalogram (EEG) signals and prevent the inspection of the underlying cognitive processes. To fuel further EEG research with speech production, a method using three-mode tensor decomposition (time x space x frequency) is proposed to perform speech artifact removal. Tensor decomposition enables simultaneous inspection of multiple modes, which suits the multi-way nature of EEG data.

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Authors:
Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura
Submitted On:
1 May 2019 - 4:29am
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Holy Lovenia - ICASSP Poster (A0).pdf

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[1] Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura, "SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3902. Accessed: Jul. 08, 2020.
@article{3902-19,
url = {http://sigport.org/3902},
author = {Holy Lovenia; Hiroki Tanaka; Sakriani Sakti; Ayu Purwarianti; Satoshi Nakamura },
publisher = {IEEE SigPort},
title = {SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION},
year = {2019} }
TY - EJOUR
T1 - SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION
AU - Holy Lovenia; Hiroki Tanaka; Sakriani Sakti; Ayu Purwarianti; Satoshi Nakamura
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3902
ER -
Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura. (2019). SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION. IEEE SigPort. http://sigport.org/3902
Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura, 2019. SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION. Available at: http://sigport.org/3902.
Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura. (2019). "SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION." Web.
1. Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura. SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3902

[Poster] Localized Random Sampling for Robust Compressive Beam Alignment


Compressed sensing (CS)-based beam alignment is a promising solution for rapid link configuration in millimeter wave (mmWave)

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Authors:
Nitin Jonathan Myers, Robert W. Heath Jr.
Submitted On:
30 April 2019 - 11:30pm
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[1] Nitin Jonathan Myers, Robert W. Heath Jr., "[Poster] Localized Random Sampling for Robust Compressive Beam Alignment", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3900. Accessed: Jul. 08, 2020.
@article{3900-19,
url = {http://sigport.org/3900},
author = {Nitin Jonathan Myers; Robert W. Heath Jr. },
publisher = {IEEE SigPort},
title = {[Poster] Localized Random Sampling for Robust Compressive Beam Alignment},
year = {2019} }
TY - EJOUR
T1 - [Poster] Localized Random Sampling for Robust Compressive Beam Alignment
AU - Nitin Jonathan Myers; Robert W. Heath Jr.
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3900
ER -
Nitin Jonathan Myers, Robert W. Heath Jr.. (2019). [Poster] Localized Random Sampling for Robust Compressive Beam Alignment. IEEE SigPort. http://sigport.org/3900
Nitin Jonathan Myers, Robert W. Heath Jr., 2019. [Poster] Localized Random Sampling for Robust Compressive Beam Alignment. Available at: http://sigport.org/3900.
Nitin Jonathan Myers, Robert W. Heath Jr.. (2019). "[Poster] Localized Random Sampling for Robust Compressive Beam Alignment." Web.
1. Nitin Jonathan Myers, Robert W. Heath Jr.. [Poster] Localized Random Sampling for Robust Compressive Beam Alignment [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3900

MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION


Millimeter wave (mmWave) massive multiple input multiple output (MIMO) systems realizing directive beamforming require reliable estimation of the wireless propagation channel. However, mmWave channels are characterized by high variability that severely challenges their recovery over short training periods. Current channel estimation techniques exploit either the channel sparsity in the beamspace domain or its low-rank property in the antenna domain, nevertheless, they still require large numbers of training symbols for the satisfactory performance.

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Authors:
E. Vlachos, G. Alexandropoulos, J. Thompson
Submitted On:
22 May 2019 - 11:17pm
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IEEE Signal Processing Letters 2018

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ICASSP19___Poster.pdf

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[1] E. Vlachos, G. Alexandropoulos, J. Thompson, "MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3899. Accessed: Jul. 08, 2020.
@article{3899-19,
url = {http://sigport.org/3899},
author = {E. Vlachos; G. Alexandropoulos; J. Thompson },
publisher = {IEEE SigPort},
title = {MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION},
year = {2019} }
TY - EJOUR
T1 - MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION
AU - E. Vlachos; G. Alexandropoulos; J. Thompson
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3899
ER -
E. Vlachos, G. Alexandropoulos, J. Thompson. (2019). MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION. IEEE SigPort. http://sigport.org/3899
E. Vlachos, G. Alexandropoulos, J. Thompson, 2019. MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION. Available at: http://sigport.org/3899.
E. Vlachos, G. Alexandropoulos, J. Thompson. (2019). "MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION." Web.
1. E. Vlachos, G. Alexandropoulos, J. Thompson. MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3899

IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN


In recent years, the successful application of Deep Learning methods to classification problems has had a huge impact in many domains. In biomedical engineering, the problem of gesture recognition based on electromyography is often addressed as an image classification problem using Convolutional Neural Networks. In this paper, we approach

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Authors:
Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras
Submitted On:
7 May 2019 - 12:59pm
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[1] Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras, "IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3898. Accessed: Jul. 08, 2020.
@article{3898-19,
url = {http://sigport.org/3898},
author = {Panagiotis Tsinganos; Bruno Cornelis; Jan Cornelis; Bart Jansen; Athanassios Skodras },
publisher = {IEEE SigPort},
title = {IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN},
year = {2019} }
TY - EJOUR
T1 - IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN
AU - Panagiotis Tsinganos; Bruno Cornelis; Jan Cornelis; Bart Jansen; Athanassios Skodras
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3898
ER -
Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras. (2019). IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN. IEEE SigPort. http://sigport.org/3898
Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras, 2019. IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN. Available at: http://sigport.org/3898.
Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras. (2019). "IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN." Web.
1. Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras. IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3898

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