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Biometrics

DuoDepth: Static Gesture Recognition with Dual Depth Sensors


Static gesture recognition is an effective non-verbal communication channel between a user and their devices; however many modern methods are sensitive to the relative pose of the user’s hands with respect to the capture device, as parts of the gesture can become occluded. We present two methodologies for gesture recognition via synchronized recording from two depth cameras to alleviate this occlusion problem.

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Authors:
Ilya Chugunov, Avideh Zakhor
Submitted On:
21 September 2019 - 2:36am
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DuoDepth ICIP 2019 Poster

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[1] Ilya Chugunov, Avideh Zakhor, "DuoDepth: Static Gesture Recognition with Dual Depth Sensors", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4801. Accessed: Nov. 21, 2019.
@article{4801-19,
url = {http://sigport.org/4801},
author = {Ilya Chugunov; Avideh Zakhor },
publisher = {IEEE SigPort},
title = {DuoDepth: Static Gesture Recognition with Dual Depth Sensors},
year = {2019} }
TY - EJOUR
T1 - DuoDepth: Static Gesture Recognition with Dual Depth Sensors
AU - Ilya Chugunov; Avideh Zakhor
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4801
ER -
Ilya Chugunov, Avideh Zakhor. (2019). DuoDepth: Static Gesture Recognition with Dual Depth Sensors. IEEE SigPort. http://sigport.org/4801
Ilya Chugunov, Avideh Zakhor, 2019. DuoDepth: Static Gesture Recognition with Dual Depth Sensors. Available at: http://sigport.org/4801.
Ilya Chugunov, Avideh Zakhor. (2019). "DuoDepth: Static Gesture Recognition with Dual Depth Sensors." Web.
1. Ilya Chugunov, Avideh Zakhor. DuoDepth: Static Gesture Recognition with Dual Depth Sensors [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4801

DYNAMIC FACIAL FEATURES FOR INHERENTLY SAFER FACE RECOGNITION


Among the many known type of intra-class variations, facial expressions are considered particularly challenging, as witnessed by the large number of methods that have been proposed to cope with them. The idea inspiring this work is that dynamic facial features (DFF) extracted from facial expressions while a sentence is pronounced, could possibly represent a salient and inherently safer biometric identifier, due to the greater difficulty in forging a time variable descriptor instead of a static one.

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Authors:
Davide Iengo, Michele Nappi, Davide Vanore
Submitted On:
18 September 2019 - 7:03pm
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Poster_Presentation_Paper #3041.pdf

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[1] Davide Iengo, Michele Nappi, Davide Vanore, "DYNAMIC FACIAL FEATURES FOR INHERENTLY SAFER FACE RECOGNITION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4669. Accessed: Nov. 21, 2019.
@article{4669-19,
url = {http://sigport.org/4669},
author = {Davide Iengo; Michele Nappi; Davide Vanore },
publisher = {IEEE SigPort},
title = {DYNAMIC FACIAL FEATURES FOR INHERENTLY SAFER FACE RECOGNITION},
year = {2019} }
TY - EJOUR
T1 - DYNAMIC FACIAL FEATURES FOR INHERENTLY SAFER FACE RECOGNITION
AU - Davide Iengo; Michele Nappi; Davide Vanore
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4669
ER -
Davide Iengo, Michele Nappi, Davide Vanore. (2019). DYNAMIC FACIAL FEATURES FOR INHERENTLY SAFER FACE RECOGNITION. IEEE SigPort. http://sigport.org/4669
Davide Iengo, Michele Nappi, Davide Vanore, 2019. DYNAMIC FACIAL FEATURES FOR INHERENTLY SAFER FACE RECOGNITION. Available at: http://sigport.org/4669.
Davide Iengo, Michele Nappi, Davide Vanore. (2019). "DYNAMIC FACIAL FEATURES FOR INHERENTLY SAFER FACE RECOGNITION." Web.
1. Davide Iengo, Michele Nappi, Davide Vanore. DYNAMIC FACIAL FEATURES FOR INHERENTLY SAFER FACE RECOGNITION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4669

A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION


State-of-the-art face recognition methods have achieved ex- cellent performance on the clean datasets. However, in real- world applications, the captured face images are usually contaminated with noise, which significantly decreases the performance of these face recognition methods. In this pa- per, we propose a cascaded noise-robust deep convolutional neural network (CNR-CNN) method, consisting of two sub- networks, i.e., a denoising sub-network and a face recognition sub-network, for face recognition under noise.

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Authors:
Xiangbang Meng,Yan Yan,Si Chen, Hanzi Wang
Submitted On:
10 September 2019 - 10:52pm
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A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION.pdf

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[1] Xiangbang Meng,Yan Yan,Si Chen, Hanzi Wang, "A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4584. Accessed: Nov. 21, 2019.
@article{4584-19,
url = {http://sigport.org/4584},
author = {Xiangbang Meng;Yan Yan;Si Chen; Hanzi Wang },
publisher = {IEEE SigPort},
title = {A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION},
year = {2019} }
TY - EJOUR
T1 - A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION
AU - Xiangbang Meng;Yan Yan;Si Chen; Hanzi Wang
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4584
ER -
Xiangbang Meng,Yan Yan,Si Chen, Hanzi Wang. (2019). A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION. IEEE SigPort. http://sigport.org/4584
Xiangbang Meng,Yan Yan,Si Chen, Hanzi Wang, 2019. A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION. Available at: http://sigport.org/4584.
Xiangbang Meng,Yan Yan,Si Chen, Hanzi Wang. (2019). "A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION." Web.
1. Xiangbang Meng,Yan Yan,Si Chen, Hanzi Wang. A CASCADED NOISE-ROBUST DEEP CNN FOR FACE RECOGNITION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4584

Securing smartphone handwritten PIN codes with recurrent neural networks

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Authors:
Gaël LE LAN, Vincent FREY
Submitted On:
15 May 2019 - 6:21am
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[1] Gaël LE LAN, Vincent FREY, "Securing smartphone handwritten PIN codes with recurrent neural networks", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4521. Accessed: Nov. 21, 2019.
@article{4521-19,
url = {http://sigport.org/4521},
author = {Gaël LE LAN; Vincent FREY },
publisher = {IEEE SigPort},
title = {Securing smartphone handwritten PIN codes with recurrent neural networks},
year = {2019} }
TY - EJOUR
T1 - Securing smartphone handwritten PIN codes with recurrent neural networks
AU - Gaël LE LAN; Vincent FREY
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4521
ER -
Gaël LE LAN, Vincent FREY. (2019). Securing smartphone handwritten PIN codes with recurrent neural networks. IEEE SigPort. http://sigport.org/4521
Gaël LE LAN, Vincent FREY, 2019. Securing smartphone handwritten PIN codes with recurrent neural networks. Available at: http://sigport.org/4521.
Gaël LE LAN, Vincent FREY. (2019). "Securing smartphone handwritten PIN codes with recurrent neural networks." Web.
1. Gaël LE LAN, Vincent FREY. Securing smartphone handwritten PIN codes with recurrent neural networks [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4521

AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION


This paper proposes a group membership verification protocol preventing the curious but honest server from reconstructing the enrolled signatures and inferring the identity of querying clients. The protocol quantizes the signatures into discrete embeddings, making reconstruction difficult. It also aggregates multiple embeddings into representative values, impeding identification. Theoretical and experimental results show the trade-off between the security and error rates.

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Authors:
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy
Submitted On:
13 May 2019 - 9:23am
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conference_poster_4.pdf

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[1] Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy, "AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4486. Accessed: Nov. 21, 2019.
@article{4486-19,
url = {http://sigport.org/4486},
author = {Marzieh Gheisari; Teddy Furon; Laurent Amsaleg; Behrooz Razeghi; Slava Voloshynovskiy },
publisher = {IEEE SigPort},
title = {AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION},
year = {2019} }
TY - EJOUR
T1 - AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION
AU - Marzieh Gheisari; Teddy Furon; Laurent Amsaleg; Behrooz Razeghi; Slava Voloshynovskiy
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4486
ER -
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. (2019). AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION. IEEE SigPort. http://sigport.org/4486
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy, 2019. AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION. Available at: http://sigport.org/4486.
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. (2019). "AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION." Web.
1. Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4486

AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION


This paper proposes a group membership verification protocol preventing the curious but honest server from reconstructing the enrolled signatures and inferring the identity of querying clients. The protocol quantizes the signatures into discrete embeddings, making reconstruction difficult. It also aggregates multiple embeddings into representative values, impeding identification. Theoretical and experimental results show the trade-off between the security and error rates.

Paper Details

Authors:
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy
Submitted On:
13 May 2019 - 9:23am
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conference_poster_4.pdf

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[1] Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy, "AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4484. Accessed: Nov. 21, 2019.
@article{4484-19,
url = {http://sigport.org/4484},
author = {Marzieh Gheisari; Teddy Furon; Laurent Amsaleg; Behrooz Razeghi; Slava Voloshynovskiy },
publisher = {IEEE SigPort},
title = {AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION},
year = {2019} }
TY - EJOUR
T1 - AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION
AU - Marzieh Gheisari; Teddy Furon; Laurent Amsaleg; Behrooz Razeghi; Slava Voloshynovskiy
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4484
ER -
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. (2019). AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION. IEEE SigPort. http://sigport.org/4484
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy, 2019. AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION. Available at: http://sigport.org/4484.
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. (2019). "AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION." Web.
1. Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4484

CLEANING ADVERSARIAL PERTURBATIONS VIA RESIDUAL GENERATIVE NETWORK FOR FACE VERIFICATION


Deep neural networks (DNNs) have recently achieved impressive performances on various applications. However, recent researches show that DNNs are vulnerable to adversarial perturbations injected into input samples. In this paper, we investigate a defense method for face verification: a deep residual generative network (ResGN) is learned to clean adversarial perturbations. We propose a novel training framework composed of ResGN, pre-trained VGG-Face network and FaceNet network.

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Authors:
Yuying Su, Guangling Sun, Weiqi Fan, Xiaofeng Lu, Zhi Liu
Submitted On:
8 May 2019 - 4:59am
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poster苏玉莹.pdf

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[1] Yuying Su, Guangling Sun, Weiqi Fan, Xiaofeng Lu, Zhi Liu, "CLEANING ADVERSARIAL PERTURBATIONS VIA RESIDUAL GENERATIVE NETWORK FOR FACE VERIFICATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4052. Accessed: Nov. 21, 2019.
@article{4052-19,
url = {http://sigport.org/4052},
author = {Yuying Su; Guangling Sun; Weiqi Fan; Xiaofeng Lu; Zhi Liu },
publisher = {IEEE SigPort},
title = {CLEANING ADVERSARIAL PERTURBATIONS VIA RESIDUAL GENERATIVE NETWORK FOR FACE VERIFICATION},
year = {2019} }
TY - EJOUR
T1 - CLEANING ADVERSARIAL PERTURBATIONS VIA RESIDUAL GENERATIVE NETWORK FOR FACE VERIFICATION
AU - Yuying Su; Guangling Sun; Weiqi Fan; Xiaofeng Lu; Zhi Liu
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4052
ER -
Yuying Su, Guangling Sun, Weiqi Fan, Xiaofeng Lu, Zhi Liu. (2019). CLEANING ADVERSARIAL PERTURBATIONS VIA RESIDUAL GENERATIVE NETWORK FOR FACE VERIFICATION. IEEE SigPort. http://sigport.org/4052
Yuying Su, Guangling Sun, Weiqi Fan, Xiaofeng Lu, Zhi Liu, 2019. CLEANING ADVERSARIAL PERTURBATIONS VIA RESIDUAL GENERATIVE NETWORK FOR FACE VERIFICATION. Available at: http://sigport.org/4052.
Yuying Su, Guangling Sun, Weiqi Fan, Xiaofeng Lu, Zhi Liu. (2019). "CLEANING ADVERSARIAL PERTURBATIONS VIA RESIDUAL GENERATIVE NETWORK FOR FACE VERIFICATION." Web.
1. Yuying Su, Guangling Sun, Weiqi Fan, Xiaofeng Lu, Zhi Liu. CLEANING ADVERSARIAL PERTURBATIONS VIA RESIDUAL GENERATIVE NETWORK FOR FACE VERIFICATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4052

DETECTION OF VOICE TRANSFORMATION SPOOFING BASED ON DENSE CONVOLUTIONAL NETWORK


Nowadays, speech spoofing is so common that it presents a great challenge to social security. Thus, it is of great significance to recognize a spoofed speech from a genuine one. Most of the current researches have focused on voice conversion (VC), synthesis and recapture which mimic a target speaker to break through ASV systems by increased false acceptance rates. However, there exists another type of spoofing, voice transformation (VT), that transforms a speech signal without a target in order ‘not to be recognized’ by increased false reject rates. VT has received much less attention.

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Authors:
Yong Wang, Zhuoyi Su
Submitted On:
8 May 2019 - 3:15am
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Paper #1311.pdf

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[1] Yong Wang, Zhuoyi Su, "DETECTION OF VOICE TRANSFORMATION SPOOFING BASED ON DENSE CONVOLUTIONAL NETWORK", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4031. Accessed: Nov. 21, 2019.
@article{4031-19,
url = {http://sigport.org/4031},
author = {Yong Wang; Zhuoyi Su },
publisher = {IEEE SigPort},
title = {DETECTION OF VOICE TRANSFORMATION SPOOFING BASED ON DENSE CONVOLUTIONAL NETWORK},
year = {2019} }
TY - EJOUR
T1 - DETECTION OF VOICE TRANSFORMATION SPOOFING BASED ON DENSE CONVOLUTIONAL NETWORK
AU - Yong Wang; Zhuoyi Su
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4031
ER -
Yong Wang, Zhuoyi Su. (2019). DETECTION OF VOICE TRANSFORMATION SPOOFING BASED ON DENSE CONVOLUTIONAL NETWORK. IEEE SigPort. http://sigport.org/4031
Yong Wang, Zhuoyi Su, 2019. DETECTION OF VOICE TRANSFORMATION SPOOFING BASED ON DENSE CONVOLUTIONAL NETWORK. Available at: http://sigport.org/4031.
Yong Wang, Zhuoyi Su. (2019). "DETECTION OF VOICE TRANSFORMATION SPOOFING BASED ON DENSE CONVOLUTIONAL NETWORK." Web.
1. Yong Wang, Zhuoyi Su. DETECTION OF VOICE TRANSFORMATION SPOOFING BASED ON DENSE CONVOLUTIONAL NETWORK [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4031

ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION


This paper introduces a deep neural network based feature extraction scheme that aims to improve the trade-off between utility and privacy in speaker classification tasks. In the proposed scenario we develop a feature representation that helps to maximize the performance of a gender classifier while minimizing additional speaker

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Rainer Martin
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8 May 2019 - 2:50am
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[1] Rainer Martin, "ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4027. Accessed: Nov. 21, 2019.
@article{4027-19,
url = {http://sigport.org/4027},
author = {Rainer Martin },
publisher = {IEEE SigPort},
title = {ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION},
year = {2019} }
TY - EJOUR
T1 - ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION
AU - Rainer Martin
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4027
ER -
Rainer Martin. (2019). ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION. IEEE SigPort. http://sigport.org/4027
Rainer Martin, 2019. ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION. Available at: http://sigport.org/4027.
Rainer Martin. (2019). "ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION." Web.
1. Rainer Martin. ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4027

ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION

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8 May 2019 - 2:50am
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[1] , "ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4025. Accessed: Nov. 21, 2019.
@article{4025-19,
url = {http://sigport.org/4025},
author = { },
publisher = {IEEE SigPort},
title = {ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION},
year = {2019} }
TY - EJOUR
T1 - ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4025
ER -
. (2019). ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION. IEEE SigPort. http://sigport.org/4025
, 2019. ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION. Available at: http://sigport.org/4025.
. (2019). "ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION." Web.
1. . ICASSP 2019 Poster for Paper #3198: PRIVACY-AWARE FEATURE EXTRACTION FOR GENDER DISCRIMINATION VERSUS SPEAKER IDENTIFICATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4025

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