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ICASSP 2020

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The ICASSP 2020 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.

CROSS LINGUAL TRANSFER LEARNING FOR ZERO-RESOURCE DOMAIN ADAPTATION


We propose a method for zero-resource domain adaptation of DNN acoustic models, for use in low-resource situations where the only in-language training data available may be poorly matched to the intended target domain. Our method uses a multi-lingual model in which several DNN layers are shared between languages. This architecture enables domain adaptation transforms learned for one well-resourced language to be applied to an entirely different low- resource language.

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Authors:
Alberto Abad, Peter Bell, Andrea Carmantini, Steve Renals
Submitted On:
22 May 2020 - 8:32am
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[1] Alberto Abad, Peter Bell, Andrea Carmantini, Steve Renals, "CROSS LINGUAL TRANSFER LEARNING FOR ZERO-RESOURCE DOMAIN ADAPTATION", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5432. Accessed: Oct. 27, 2020.
@article{5432-20,
url = {http://sigport.org/5432},
author = {Alberto Abad; Peter Bell; Andrea Carmantini; Steve Renals },
publisher = {IEEE SigPort},
title = {CROSS LINGUAL TRANSFER LEARNING FOR ZERO-RESOURCE DOMAIN ADAPTATION},
year = {2020} }
TY - EJOUR
T1 - CROSS LINGUAL TRANSFER LEARNING FOR ZERO-RESOURCE DOMAIN ADAPTATION
AU - Alberto Abad; Peter Bell; Andrea Carmantini; Steve Renals
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5432
ER -
Alberto Abad, Peter Bell, Andrea Carmantini, Steve Renals. (2020). CROSS LINGUAL TRANSFER LEARNING FOR ZERO-RESOURCE DOMAIN ADAPTATION. IEEE SigPort. http://sigport.org/5432
Alberto Abad, Peter Bell, Andrea Carmantini, Steve Renals, 2020. CROSS LINGUAL TRANSFER LEARNING FOR ZERO-RESOURCE DOMAIN ADAPTATION. Available at: http://sigport.org/5432.
Alberto Abad, Peter Bell, Andrea Carmantini, Steve Renals. (2020). "CROSS LINGUAL TRANSFER LEARNING FOR ZERO-RESOURCE DOMAIN ADAPTATION." Web.
1. Alberto Abad, Peter Bell, Andrea Carmantini, Steve Renals. CROSS LINGUAL TRANSFER LEARNING FOR ZERO-RESOURCE DOMAIN ADAPTATION [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5432

On the Stability of Polynomial Spectral Graph Filters

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Authors:
Henry Kenlay, Dorina Thanou, Xiaowen Dong
Submitted On:
22 May 2020 - 5:17am
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[1] Henry Kenlay, Dorina Thanou, Xiaowen Dong, "On the Stability of Polynomial Spectral Graph Filters", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5431. Accessed: Oct. 27, 2020.
@article{5431-20,
url = {http://sigport.org/5431},
author = {Henry Kenlay; Dorina Thanou; Xiaowen Dong },
publisher = {IEEE SigPort},
title = {On the Stability of Polynomial Spectral Graph Filters},
year = {2020} }
TY - EJOUR
T1 - On the Stability of Polynomial Spectral Graph Filters
AU - Henry Kenlay; Dorina Thanou; Xiaowen Dong
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5431
ER -
Henry Kenlay, Dorina Thanou, Xiaowen Dong. (2020). On the Stability of Polynomial Spectral Graph Filters. IEEE SigPort. http://sigport.org/5431
Henry Kenlay, Dorina Thanou, Xiaowen Dong, 2020. On the Stability of Polynomial Spectral Graph Filters. Available at: http://sigport.org/5431.
Henry Kenlay, Dorina Thanou, Xiaowen Dong. (2020). "On the Stability of Polynomial Spectral Graph Filters." Web.
1. Henry Kenlay, Dorina Thanou, Xiaowen Dong. On the Stability of Polynomial Spectral Graph Filters [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5431

MULTI-HEAD ATTENTION FOR SPEECH EMOTION RECOGNITION WITH AUXILIARY LEARNING OF GENDER RECOGNITION


The paper presents a Multi-Head Attention deep learning network for Speech Emotion Recognition (SER) using Log mel-Filter Bank Energies (LFBE) spectral features as the input. The multi-head attention along with the position embedding jointly attends to information from different representations of the same LFBE input sequence. The position embedding helps in attending to the dominant emotion features by identifying positions of the features in the sequence. In addition to Multi-Head Attention and position embedding, we apply multi-task learning with gender recognition as an auxiliary task.

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Authors:
Periyasamy Paramasivam, Promod Yenigalla
Submitted On:
21 May 2020 - 11:36pm
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[1] Periyasamy Paramasivam, Promod Yenigalla, "MULTI-HEAD ATTENTION FOR SPEECH EMOTION RECOGNITION WITH AUXILIARY LEARNING OF GENDER RECOGNITION", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5430. Accessed: Oct. 27, 2020.
@article{5430-20,
url = {http://sigport.org/5430},
author = {Periyasamy Paramasivam; Promod Yenigalla },
publisher = {IEEE SigPort},
title = {MULTI-HEAD ATTENTION FOR SPEECH EMOTION RECOGNITION WITH AUXILIARY LEARNING OF GENDER RECOGNITION},
year = {2020} }
TY - EJOUR
T1 - MULTI-HEAD ATTENTION FOR SPEECH EMOTION RECOGNITION WITH AUXILIARY LEARNING OF GENDER RECOGNITION
AU - Periyasamy Paramasivam; Promod Yenigalla
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5430
ER -
Periyasamy Paramasivam, Promod Yenigalla. (2020). MULTI-HEAD ATTENTION FOR SPEECH EMOTION RECOGNITION WITH AUXILIARY LEARNING OF GENDER RECOGNITION. IEEE SigPort. http://sigport.org/5430
Periyasamy Paramasivam, Promod Yenigalla, 2020. MULTI-HEAD ATTENTION FOR SPEECH EMOTION RECOGNITION WITH AUXILIARY LEARNING OF GENDER RECOGNITION. Available at: http://sigport.org/5430.
Periyasamy Paramasivam, Promod Yenigalla. (2020). "MULTI-HEAD ATTENTION FOR SPEECH EMOTION RECOGNITION WITH AUXILIARY LEARNING OF GENDER RECOGNITION." Web.
1. Periyasamy Paramasivam, Promod Yenigalla. MULTI-HEAD ATTENTION FOR SPEECH EMOTION RECOGNITION WITH AUXILIARY LEARNING OF GENDER RECOGNITION [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5430

Combining cGAN and MIL for Hotspot Segmentation in Bone Scintigraphy

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Authors:
Hang Xu, Shijie Geng, Yu Qiao, Kuan Xu, Yueyang Gu
Submitted On:
21 May 2020 - 11:00pm
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Paper 2748 ICASSP 2020.pdf

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[1] Hang Xu, Shijie Geng, Yu Qiao, Kuan Xu, Yueyang Gu, "Combining cGAN and MIL for Hotspot Segmentation in Bone Scintigraphy", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5429. Accessed: Oct. 27, 2020.
@article{5429-20,
url = {http://sigport.org/5429},
author = {Hang Xu; Shijie Geng; Yu Qiao; Kuan Xu; Yueyang Gu },
publisher = {IEEE SigPort},
title = {Combining cGAN and MIL for Hotspot Segmentation in Bone Scintigraphy},
year = {2020} }
TY - EJOUR
T1 - Combining cGAN and MIL for Hotspot Segmentation in Bone Scintigraphy
AU - Hang Xu; Shijie Geng; Yu Qiao; Kuan Xu; Yueyang Gu
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5429
ER -
Hang Xu, Shijie Geng, Yu Qiao, Kuan Xu, Yueyang Gu. (2020). Combining cGAN and MIL for Hotspot Segmentation in Bone Scintigraphy. IEEE SigPort. http://sigport.org/5429
Hang Xu, Shijie Geng, Yu Qiao, Kuan Xu, Yueyang Gu, 2020. Combining cGAN and MIL for Hotspot Segmentation in Bone Scintigraphy. Available at: http://sigport.org/5429.
Hang Xu, Shijie Geng, Yu Qiao, Kuan Xu, Yueyang Gu. (2020). "Combining cGAN and MIL for Hotspot Segmentation in Bone Scintigraphy." Web.
1. Hang Xu, Shijie Geng, Yu Qiao, Kuan Xu, Yueyang Gu. Combining cGAN and MIL for Hotspot Segmentation in Bone Scintigraphy [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5429

Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning


In this paper, we propose a communication-efficient decentralized machine learning (ML) algorithm, coined quantized group ADMM (Q-GADMM). Every worker in Q-GADMM communicates only with two neighbors, and updates its model via the group alternating direct method of multiplier (GADMM), thereby ensuring fast convergence while reducing the number of communication rounds. Furthermore, each worker quantizes its model updates before transmissions, thereby decreasing the communication payload sizes.

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Authors:
Anis Elgabli, Jihong Park, Amrit Bedi, Mehdi Bennis, Vaneet Aggarwal
Submitted On:
21 May 2020 - 3:34pm
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[1] Anis Elgabli, Jihong Park, Amrit Bedi, Mehdi Bennis, Vaneet Aggarwal, "Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5428. Accessed: Oct. 27, 2020.
@article{5428-20,
url = {http://sigport.org/5428},
author = {Anis Elgabli; Jihong Park; Amrit Bedi; Mehdi Bennis; Vaneet Aggarwal },
publisher = {IEEE SigPort},
title = {Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning},
year = {2020} }
TY - EJOUR
T1 - Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning
AU - Anis Elgabli; Jihong Park; Amrit Bedi; Mehdi Bennis; Vaneet Aggarwal
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5428
ER -
Anis Elgabli, Jihong Park, Amrit Bedi, Mehdi Bennis, Vaneet Aggarwal. (2020). Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning. IEEE SigPort. http://sigport.org/5428
Anis Elgabli, Jihong Park, Amrit Bedi, Mehdi Bennis, Vaneet Aggarwal, 2020. Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning. Available at: http://sigport.org/5428.
Anis Elgabli, Jihong Park, Amrit Bedi, Mehdi Bennis, Vaneet Aggarwal. (2020). "Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning." Web.
1. Anis Elgabli, Jihong Park, Amrit Bedi, Mehdi Bennis, Vaneet Aggarwal. Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5428

Optimizing Bayesian HMM Based x-vector Clustering for theSecond DIHARD Speech Diarization Challenge

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Authors:
Mireia Diez, Lukas Burget, Federico Landini, Shuai Wang, Honza Cernocky
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21 May 2020 - 9:13am
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[1] Mireia Diez, Lukas Burget, Federico Landini, Shuai Wang, Honza Cernocky, "Optimizing Bayesian HMM Based x-vector Clustering for theSecond DIHARD Speech Diarization Challenge", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5427. Accessed: Oct. 27, 2020.
@article{5427-20,
url = {http://sigport.org/5427},
author = {Mireia Diez; Lukas Burget; Federico Landini; Shuai Wang; Honza Cernocky },
publisher = {IEEE SigPort},
title = {Optimizing Bayesian HMM Based x-vector Clustering for theSecond DIHARD Speech Diarization Challenge},
year = {2020} }
TY - EJOUR
T1 - Optimizing Bayesian HMM Based x-vector Clustering for theSecond DIHARD Speech Diarization Challenge
AU - Mireia Diez; Lukas Burget; Federico Landini; Shuai Wang; Honza Cernocky
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5427
ER -
Mireia Diez, Lukas Burget, Federico Landini, Shuai Wang, Honza Cernocky. (2020). Optimizing Bayesian HMM Based x-vector Clustering for theSecond DIHARD Speech Diarization Challenge. IEEE SigPort. http://sigport.org/5427
Mireia Diez, Lukas Burget, Federico Landini, Shuai Wang, Honza Cernocky, 2020. Optimizing Bayesian HMM Based x-vector Clustering for theSecond DIHARD Speech Diarization Challenge. Available at: http://sigport.org/5427.
Mireia Diez, Lukas Burget, Federico Landini, Shuai Wang, Honza Cernocky. (2020). "Optimizing Bayesian HMM Based x-vector Clustering for theSecond DIHARD Speech Diarization Challenge." Web.
1. Mireia Diez, Lukas Burget, Federico Landini, Shuai Wang, Honza Cernocky. Optimizing Bayesian HMM Based x-vector Clustering for theSecond DIHARD Speech Diarization Challenge [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5427

Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking


The purpose of this study is to detect the mismatch between text script and voice-over. For this, we present a novel utterance verification (UV) method, which calculates the degree of correspondence between a voice-over and the phoneme sequence of a script. We found that the phoneme recognition probabilities of exaggerated voice-overs decrease compared to ordinary utterances, but their rankings do not demonstrate any significant change.

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Authors:
Yoonjae Jeong, Hoon-Young Cho
Submitted On:
21 May 2020 - 7:57am
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[1] Yoonjae Jeong, Hoon-Young Cho, "Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5426. Accessed: Oct. 27, 2020.
@article{5426-20,
url = {http://sigport.org/5426},
author = {Yoonjae Jeong; Hoon-Young Cho },
publisher = {IEEE SigPort},
title = {Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking},
year = {2020} }
TY - EJOUR
T1 - Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking
AU - Yoonjae Jeong; Hoon-Young Cho
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5426
ER -
Yoonjae Jeong, Hoon-Young Cho. (2020). Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking. IEEE SigPort. http://sigport.org/5426
Yoonjae Jeong, Hoon-Young Cho, 2020. Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking. Available at: http://sigport.org/5426.
Yoonjae Jeong, Hoon-Young Cho. (2020). "Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking." Web.
1. Yoonjae Jeong, Hoon-Young Cho. Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5426

Detection of Malicious VBScript Using Static and Dynamic Analysis with Recurrent Deep Learning

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Authors:
Jack W. Stokes, Rakshit Agrawal, Geoff McDonald
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21 May 2020 - 1:25am
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[1] Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, "Detection of Malicious VBScript Using Static and Dynamic Analysis with Recurrent Deep Learning", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5425. Accessed: Oct. 27, 2020.
@article{5425-20,
url = {http://sigport.org/5425},
author = {Jack W. Stokes; Rakshit Agrawal; Geoff McDonald },
publisher = {IEEE SigPort},
title = {Detection of Malicious VBScript Using Static and Dynamic Analysis with Recurrent Deep Learning},
year = {2020} }
TY - EJOUR
T1 - Detection of Malicious VBScript Using Static and Dynamic Analysis with Recurrent Deep Learning
AU - Jack W. Stokes; Rakshit Agrawal; Geoff McDonald
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5425
ER -
Jack W. Stokes, Rakshit Agrawal, Geoff McDonald. (2020). Detection of Malicious VBScript Using Static and Dynamic Analysis with Recurrent Deep Learning. IEEE SigPort. http://sigport.org/5425
Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, 2020. Detection of Malicious VBScript Using Static and Dynamic Analysis with Recurrent Deep Learning. Available at: http://sigport.org/5425.
Jack W. Stokes, Rakshit Agrawal, Geoff McDonald. (2020). "Detection of Malicious VBScript Using Static and Dynamic Analysis with Recurrent Deep Learning." Web.
1. Jack W. Stokes, Rakshit Agrawal, Geoff McDonald. Detection of Malicious VBScript Using Static and Dynamic Analysis with Recurrent Deep Learning [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5425

Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption

Paper Details

Authors:
Edward J. Chou, Arun Gururajan, Kim Laine, Nitin Kumar Goel, Anna Bertiger, Jack W. Stokes
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21 May 2020 - 1:29am
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[1] Edward J. Chou, Arun Gururajan, Kim Laine, Nitin Kumar Goel, Anna Bertiger, Jack W. Stokes, "Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5424. Accessed: Oct. 27, 2020.
@article{5424-20,
url = {http://sigport.org/5424},
author = {Edward J. Chou; Arun Gururajan; Kim Laine; Nitin Kumar Goel; Anna Bertiger; Jack W. Stokes },
publisher = {IEEE SigPort},
title = {Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption},
year = {2020} }
TY - EJOUR
T1 - Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption
AU - Edward J. Chou; Arun Gururajan; Kim Laine; Nitin Kumar Goel; Anna Bertiger; Jack W. Stokes
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5424
ER -
Edward J. Chou, Arun Gururajan, Kim Laine, Nitin Kumar Goel, Anna Bertiger, Jack W. Stokes. (2020). Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption. IEEE SigPort. http://sigport.org/5424
Edward J. Chou, Arun Gururajan, Kim Laine, Nitin Kumar Goel, Anna Bertiger, Jack W. Stokes, 2020. Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption. Available at: http://sigport.org/5424.
Edward J. Chou, Arun Gururajan, Kim Laine, Nitin Kumar Goel, Anna Bertiger, Jack W. Stokes. (2020). "Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption." Web.
1. Edward J. Chou, Arun Gururajan, Kim Laine, Nitin Kumar Goel, Anna Bertiger, Jack W. Stokes. Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5424

'TEXCEPTION: A Character/Word-Level Deep Learning Model for Phishing URL Detection

Paper Details

Authors:
Farid Tajaddodianfar, Jack W. Stokes, Arun Gururajan
Submitted On:
21 May 2020 - 1:35am
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texception_icassp_presentation.pdf

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[1] Farid Tajaddodianfar, Jack W. Stokes, Arun Gururajan, "'TEXCEPTION: A Character/Word-Level Deep Learning Model for Phishing URL Detection", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5423. Accessed: Oct. 27, 2020.
@article{5423-20,
url = {http://sigport.org/5423},
author = {Farid Tajaddodianfar; Jack W. Stokes; Arun Gururajan },
publisher = {IEEE SigPort},
title = {'TEXCEPTION: A Character/Word-Level Deep Learning Model for Phishing URL Detection},
year = {2020} }
TY - EJOUR
T1 - 'TEXCEPTION: A Character/Word-Level Deep Learning Model for Phishing URL Detection
AU - Farid Tajaddodianfar; Jack W. Stokes; Arun Gururajan
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5423
ER -
Farid Tajaddodianfar, Jack W. Stokes, Arun Gururajan. (2020). 'TEXCEPTION: A Character/Word-Level Deep Learning Model for Phishing URL Detection. IEEE SigPort. http://sigport.org/5423
Farid Tajaddodianfar, Jack W. Stokes, Arun Gururajan, 2020. 'TEXCEPTION: A Character/Word-Level Deep Learning Model for Phishing URL Detection. Available at: http://sigport.org/5423.
Farid Tajaddodianfar, Jack W. Stokes, Arun Gururajan. (2020). "'TEXCEPTION: A Character/Word-Level Deep Learning Model for Phishing URL Detection." Web.
1. Farid Tajaddodianfar, Jack W. Stokes, Arun Gururajan. 'TEXCEPTION: A Character/Word-Level Deep Learning Model for Phishing URL Detection [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5423

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