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GlobalSIP 2019

The 7th IEEE Global Conference on Signal and Information Processing (GlobalSIP)  focuses on signal and information processing with an emphasis on up-and-coming signal processing themes. The conference features world-class plenary speeches, distinguished symposium talks, tutorials, exhibits, oral and poster sessions, and panels. GlobalSIP is comprised of co-located General Symposium and symposia selected based on responses to the call-for-symposia proposals.

MAC ID Spoofing-Resistant Radio Fingerprinting


We explore the resistance of deep learning methods for radio fingerprinting to MAC ID spoofing. We demonstrate that classifying transmission slices enables classification of a transmission with a fixed-length input deep classifier, enhances shift-invariance, and, most importantly, makes the classifier resistant to MAC ID spoofing. This is a consequence of the fact that the classifier does not learn to use the MAC ID to classifying among transmissions, but relies on other inherent discriminating signals, e.g., device imperfections.

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Authors:
Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer Dy, Kaushik Chowdhury, Stratis Ioannidis
Submitted On:
11 November 2019 - 9:13pm
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[1] Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer Dy, Kaushik Chowdhury, Stratis Ioannidis, "MAC ID Spoofing-Resistant Radio Fingerprinting", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4948. Accessed: Nov. 11, 2019.
@article{4948-19,
url = {http://sigport.org/4948},
author = {Tong Jian; Bruno Costa Rendon; Andrey Gritsenko; Jennifer Dy; Kaushik Chowdhury; Stratis Ioannidis },
publisher = {IEEE SigPort},
title = {MAC ID Spoofing-Resistant Radio Fingerprinting},
year = {2019} }
TY - EJOUR
T1 - MAC ID Spoofing-Resistant Radio Fingerprinting
AU - Tong Jian; Bruno Costa Rendon; Andrey Gritsenko; Jennifer Dy; Kaushik Chowdhury; Stratis Ioannidis
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4948
ER -
Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer Dy, Kaushik Chowdhury, Stratis Ioannidis. (2019). MAC ID Spoofing-Resistant Radio Fingerprinting. IEEE SigPort. http://sigport.org/4948
Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer Dy, Kaushik Chowdhury, Stratis Ioannidis, 2019. MAC ID Spoofing-Resistant Radio Fingerprinting. Available at: http://sigport.org/4948.
Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer Dy, Kaushik Chowdhury, Stratis Ioannidis. (2019). "MAC ID Spoofing-Resistant Radio Fingerprinting." Web.
1. Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer Dy, Kaushik Chowdhury, Stratis Ioannidis. MAC ID Spoofing-Resistant Radio Fingerprinting [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4948

3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors


Integration of multi-chip cascaded multiple-input multiple-output (MIMO) millimeter-wave (mmWave) sensors with synthetic aperture radar (SAR) imaging will enable cost-effective and scalable solutions for a variety of applications including security, automotive, and surveillance. In this paper, the first three-dimensional (3-D) holographic MIMO-SAR imaging system using cascaded mmWave sensors is designed and implemented. The challenges imposed by the use of cascaded mmWave sensors in high-resolution MIMO-SAR imaging systems are discussed.

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Authors:
Muhammet Emin Yanik, Dan Wang, Murat Torlak
Submitted On:
11 November 2019 - 8:34pm
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3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors.pdf

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[1] Muhammet Emin Yanik, Dan Wang, Murat Torlak, "3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4947. Accessed: Nov. 11, 2019.
@article{4947-19,
url = {http://sigport.org/4947},
author = {Muhammet Emin Yanik; Dan Wang; Murat Torlak },
publisher = {IEEE SigPort},
title = {3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors},
year = {2019} }
TY - EJOUR
T1 - 3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors
AU - Muhammet Emin Yanik; Dan Wang; Murat Torlak
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4947
ER -
Muhammet Emin Yanik, Dan Wang, Murat Torlak. (2019). 3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors. IEEE SigPort. http://sigport.org/4947
Muhammet Emin Yanik, Dan Wang, Murat Torlak, 2019. 3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors. Available at: http://sigport.org/4947.
Muhammet Emin Yanik, Dan Wang, Murat Torlak. (2019). "3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors." Web.
1. Muhammet Emin Yanik, Dan Wang, Murat Torlak. 3-D MIMO-SAR Imaging Using Multi-Chip Cascaded Millimeter-Wave Sensors [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4947

Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos


Research has shown that caregivers implementing
pivotal response treatment (PRT) with their child with autism
spectrum disorder (ASD) helps the child develop social and
communication skills. Evaluation of caregiver fidelity to PRT in
training programs and research studies relies on the evaluation
of video probes depicting the caregiver interacting with his
or her child. These video probes are reviewed by behavior
analysts and are dependent on manual processing to extract
data metrics. Using multimodal data processing techniques and

Paper Details

Authors:
Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan
Submitted On:
11 November 2019 - 8:34pm
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[1] Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan, "Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4946. Accessed: Nov. 11, 2019.
@article{4946-19,
url = {http://sigport.org/4946},
author = {Corey Heath; Hemanth Venkateswara; Troy McDaniel; Sethuraman Panchanathan },
publisher = {IEEE SigPort},
title = {Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos},
year = {2019} }
TY - EJOUR
T1 - Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos
AU - Corey Heath; Hemanth Venkateswara; Troy McDaniel; Sethuraman Panchanathan
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4946
ER -
Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan. (2019). Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos. IEEE SigPort. http://sigport.org/4946
Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan, 2019. Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos. Available at: http://sigport.org/4946.
Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan. (2019). "Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos." Web.
1. Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan. Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4946

Exploiting Structural Information in Camera Aided Radar Parameter Estimation


The sparse nature of the ranging and spatial angle
parameter space has been exploited by many radar parameter
estimation algorithms in literature. We note that real world
reflections are not sporadically sparse in the parameter space and
typically exhibit smooth variation effects with non-zero entries
occurring in clusters. In this paper, we explicitly model this
additional structural information into our estimation algorithm
and propose a non-convex regularization of the linear observation

Paper Details

Authors:
Khurram Usman Mazher, Ramakrishna Sai Annaluru, Amine Mezghani, Robert Heath
Submitted On:
11 November 2019 - 11:28am
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Exploiting Structural Information in Camera Aided Radar Parameter Estimation.pdf

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[1] Khurram Usman Mazher, Ramakrishna Sai Annaluru, Amine Mezghani, Robert Heath , "Exploiting Structural Information in Camera Aided Radar Parameter Estimation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4945. Accessed: Nov. 11, 2019.
@article{4945-19,
url = {http://sigport.org/4945},
author = {Khurram Usman Mazher; Ramakrishna Sai Annaluru; Amine Mezghani; Robert Heath },
publisher = {IEEE SigPort},
title = {Exploiting Structural Information in Camera Aided Radar Parameter Estimation},
year = {2019} }
TY - EJOUR
T1 - Exploiting Structural Information in Camera Aided Radar Parameter Estimation
AU - Khurram Usman Mazher; Ramakrishna Sai Annaluru; Amine Mezghani; Robert Heath
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4945
ER -
Khurram Usman Mazher, Ramakrishna Sai Annaluru, Amine Mezghani, Robert Heath . (2019). Exploiting Structural Information in Camera Aided Radar Parameter Estimation. IEEE SigPort. http://sigport.org/4945
Khurram Usman Mazher, Ramakrishna Sai Annaluru, Amine Mezghani, Robert Heath , 2019. Exploiting Structural Information in Camera Aided Radar Parameter Estimation. Available at: http://sigport.org/4945.
Khurram Usman Mazher, Ramakrishna Sai Annaluru, Amine Mezghani, Robert Heath . (2019). "Exploiting Structural Information in Camera Aided Radar Parameter Estimation." Web.
1. Khurram Usman Mazher, Ramakrishna Sai Annaluru, Amine Mezghani, Robert Heath . Exploiting Structural Information in Camera Aided Radar Parameter Estimation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4945

$\alpha$ Belief Propagation as Fully Factorized Approximation

Paper Details

Authors:
Dong Liu, Nima N. Moghadam, Lars Kildehoj Rasmussen, Saikat ChatterjeeJingliang Huang,
Submitted On:
10 November 2019 - 12:06pm
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[1] Dong Liu, Nima N. Moghadam, Lars Kildehoj Rasmussen, Saikat ChatterjeeJingliang Huang, , "$\alpha$ Belief Propagation as Fully Factorized Approximation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4944. Accessed: Nov. 11, 2019.
@article{4944-19,
url = {http://sigport.org/4944},
author = {Dong Liu; Nima N. Moghadam; Lars Kildehoj Rasmussen; Saikat ChatterjeeJingliang Huang; },
publisher = {IEEE SigPort},
title = {$\alpha$ Belief Propagation as Fully Factorized Approximation},
year = {2019} }
TY - EJOUR
T1 - $\alpha$ Belief Propagation as Fully Factorized Approximation
AU - Dong Liu; Nima N. Moghadam; Lars Kildehoj Rasmussen; Saikat ChatterjeeJingliang Huang;
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4944
ER -
Dong Liu, Nima N. Moghadam, Lars Kildehoj Rasmussen, Saikat ChatterjeeJingliang Huang, . (2019). $\alpha$ Belief Propagation as Fully Factorized Approximation. IEEE SigPort. http://sigport.org/4944
Dong Liu, Nima N. Moghadam, Lars Kildehoj Rasmussen, Saikat ChatterjeeJingliang Huang, , 2019. $\alpha$ Belief Propagation as Fully Factorized Approximation. Available at: http://sigport.org/4944.
Dong Liu, Nima N. Moghadam, Lars Kildehoj Rasmussen, Saikat ChatterjeeJingliang Huang, . (2019). "$\alpha$ Belief Propagation as Fully Factorized Approximation." Web.
1. Dong Liu, Nima N. Moghadam, Lars Kildehoj Rasmussen, Saikat ChatterjeeJingliang Huang, . $\alpha$ Belief Propagation as Fully Factorized Approximation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4944

FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network


High dynamic range (HDR) image generation from a single exposure low dynamic range (LDR) image has been made possible due to the recent advances in Deep Learning. Various feed-forward Convolutional Neural Networks (CNNs) have been proposed for learning LDR to HDR representations. To better utilize the power of CNNs, we exploit the idea of feedback, where the initial low level features are guided by the high level features using a hidden state of a Recurrent Neural Network.

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Authors:
Zeeshan Khan, Mukul Khanna, Shanmuganathan Raman
Submitted On:
10 November 2019 - 4:07am
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[1] Zeeshan Khan, Mukul Khanna, Shanmuganathan Raman, "FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4943. Accessed: Nov. 11, 2019.
@article{4943-19,
url = {http://sigport.org/4943},
author = {Zeeshan Khan; Mukul Khanna; Shanmuganathan Raman },
publisher = {IEEE SigPort},
title = {FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network},
year = {2019} }
TY - EJOUR
T1 - FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network
AU - Zeeshan Khan; Mukul Khanna; Shanmuganathan Raman
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4943
ER -
Zeeshan Khan, Mukul Khanna, Shanmuganathan Raman. (2019). FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network. IEEE SigPort. http://sigport.org/4943
Zeeshan Khan, Mukul Khanna, Shanmuganathan Raman, 2019. FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network. Available at: http://sigport.org/4943.
Zeeshan Khan, Mukul Khanna, Shanmuganathan Raman. (2019). "FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network." Web.
1. Zeeshan Khan, Mukul Khanna, Shanmuganathan Raman. FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4943

Poster: Generative-Discriminative Crop Type Identification using Satellite Images


Crop type identification refers to distinguishing certain crop from other landcovers, which is an essential and crucial task in agricultural monitoring. Satellite images are good data input for identifying different crops since satellites capture relatively wider area and more spectral information. Based on prior knowledge of crop phenology, multi-temporal images are stacked to extract the growth pattern of varied crops.

Paper Details

Authors:
Nan Qiao, Yi Zhao, Ruei-Sung Lin, Bo Gong, Zhongxiang Wu, Mei Han, Jiashu Liu
Submitted On:
9 November 2019 - 7:23pm
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Poster: Generative-Discriminative Crop Type Identification using Satellite Images

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[1] Nan Qiao, Yi Zhao, Ruei-Sung Lin, Bo Gong, Zhongxiang Wu, Mei Han, Jiashu Liu, "Poster: Generative-Discriminative Crop Type Identification using Satellite Images", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4942. Accessed: Nov. 11, 2019.
@article{4942-19,
url = {http://sigport.org/4942},
author = {Nan Qiao; Yi Zhao; Ruei-Sung Lin; Bo Gong; Zhongxiang Wu; Mei Han; Jiashu Liu },
publisher = {IEEE SigPort},
title = {Poster: Generative-Discriminative Crop Type Identification using Satellite Images},
year = {2019} }
TY - EJOUR
T1 - Poster: Generative-Discriminative Crop Type Identification using Satellite Images
AU - Nan Qiao; Yi Zhao; Ruei-Sung Lin; Bo Gong; Zhongxiang Wu; Mei Han; Jiashu Liu
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4942
ER -
Nan Qiao, Yi Zhao, Ruei-Sung Lin, Bo Gong, Zhongxiang Wu, Mei Han, Jiashu Liu. (2019). Poster: Generative-Discriminative Crop Type Identification using Satellite Images. IEEE SigPort. http://sigport.org/4942
Nan Qiao, Yi Zhao, Ruei-Sung Lin, Bo Gong, Zhongxiang Wu, Mei Han, Jiashu Liu, 2019. Poster: Generative-Discriminative Crop Type Identification using Satellite Images. Available at: http://sigport.org/4942.
Nan Qiao, Yi Zhao, Ruei-Sung Lin, Bo Gong, Zhongxiang Wu, Mei Han, Jiashu Liu. (2019). "Poster: Generative-Discriminative Crop Type Identification using Satellite Images." Web.
1. Nan Qiao, Yi Zhao, Ruei-Sung Lin, Bo Gong, Zhongxiang Wu, Mei Han, Jiashu Liu. Poster: Generative-Discriminative Crop Type Identification using Satellite Images [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4942

Combining TD-IDF with symptom features to differentiate between lymphoma and tuberculosis case reports

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Authors:
Moanda Diana Pholo, Yskandar Hamam, AbdelBaset Khalaf, Chunling Du
Submitted On:
9 November 2019 - 3:41pm
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globalsip-2019-Slide-Diana-v2.pdf

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[1] Moanda Diana Pholo, Yskandar Hamam, AbdelBaset Khalaf, Chunling Du, "Combining TD-IDF with symptom features to differentiate between lymphoma and tuberculosis case reports", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4941. Accessed: Nov. 11, 2019.
@article{4941-19,
url = {http://sigport.org/4941},
author = {Moanda Diana Pholo; Yskandar Hamam; AbdelBaset Khalaf; Chunling Du },
publisher = {IEEE SigPort},
title = {Combining TD-IDF with symptom features to differentiate between lymphoma and tuberculosis case reports},
year = {2019} }
TY - EJOUR
T1 - Combining TD-IDF with symptom features to differentiate between lymphoma and tuberculosis case reports
AU - Moanda Diana Pholo; Yskandar Hamam; AbdelBaset Khalaf; Chunling Du
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4941
ER -
Moanda Diana Pholo, Yskandar Hamam, AbdelBaset Khalaf, Chunling Du. (2019). Combining TD-IDF with symptom features to differentiate between lymphoma and tuberculosis case reports. IEEE SigPort. http://sigport.org/4941
Moanda Diana Pholo, Yskandar Hamam, AbdelBaset Khalaf, Chunling Du, 2019. Combining TD-IDF with symptom features to differentiate between lymphoma and tuberculosis case reports. Available at: http://sigport.org/4941.
Moanda Diana Pholo, Yskandar Hamam, AbdelBaset Khalaf, Chunling Du. (2019). "Combining TD-IDF with symptom features to differentiate between lymphoma and tuberculosis case reports." Web.
1. Moanda Diana Pholo, Yskandar Hamam, AbdelBaset Khalaf, Chunling Du. Combining TD-IDF with symptom features to differentiate between lymphoma and tuberculosis case reports [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4941

An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition


In this paper, we examine the problem of modeling overdispersed frequency vectors that are naturally generated by several machine learning and computer vision applications.

Paper Details

Authors:
Nuha Zamzami, and Nizar Bouguila
Submitted On:
9 November 2019 - 7:08am
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[1] Nuha Zamzami, and Nizar Bouguila , "An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4940. Accessed: Nov. 11, 2019.
@article{4940-19,
url = {http://sigport.org/4940},
author = {Nuha Zamzami; and Nizar Bouguila },
publisher = {IEEE SigPort},
title = {An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition},
year = {2019} }
TY - EJOUR
T1 - An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition
AU - Nuha Zamzami; and Nizar Bouguila
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4940
ER -
Nuha Zamzami, and Nizar Bouguila . (2019). An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition. IEEE SigPort. http://sigport.org/4940
Nuha Zamzami, and Nizar Bouguila , 2019. An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition. Available at: http://sigport.org/4940.
Nuha Zamzami, and Nizar Bouguila . (2019). "An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition." Web.
1. Nuha Zamzami, and Nizar Bouguila . An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4940

An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition


In this paper, we examine the problem of modeling overdispersed frequency vectors that are naturally generated by several machine learning and computer vision applications.

Paper Details

Authors:
Nuha Zamzami, and Nizar Bouguila
Submitted On:
9 November 2019 - 7:05am
Short Link:
Type:
Event:
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MSD_Mesh.pdf

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[1] Nuha Zamzami, and Nizar Bouguila , "An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4939. Accessed: Nov. 11, 2019.
@article{4939-19,
url = {http://sigport.org/4939},
author = {Nuha Zamzami; and Nizar Bouguila },
publisher = {IEEE SigPort},
title = {An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition},
year = {2019} }
TY - EJOUR
T1 - An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition
AU - Nuha Zamzami; and Nizar Bouguila
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4939
ER -
Nuha Zamzami, and Nizar Bouguila . (2019). An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition. IEEE SigPort. http://sigport.org/4939
Nuha Zamzami, and Nizar Bouguila , 2019. An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition. Available at: http://sigport.org/4939.
Nuha Zamzami, and Nizar Bouguila . (2019). "An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition." Web.
1. Nuha Zamzami, and Nizar Bouguila . An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4939

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