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Mohamed Amine Hmani - IEEE Xplore Author Profile
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Mohamed Amine Hmani

Also published under: M. A. Hmani

Publications
5
Citations
16
Publications by Year
20182020
Co-Authors:
Show All Co-Authors (18)
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Mohamed Amine Hmani

Also published under: M. A. Hmani

Affiliation

Institut Polytechnique de Paris,Télécom SudParis, France

Publication Topics

Publications
5
Citations
16
Publications by Year
20182020
Co-Authors:
Show All Co-Authors (18)
Author's Published Works

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Evaluation of the H2020 SpeechXRays project Cancelable Face System Under the Framework of ISO/IEC 24745:2011

Mohamed Amine Hmani;Aymen Mtibaa;Dijana Petrovska-Delacrtaz;Claude Bauzou;Iacob Crucianu

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
Thanks to the recent advances in deep learning and the availability of big datasets, biometric systems boast of having high performance. However, these systems suffer from two main shortcomings, non-revocability, and vulnerability to biometric spoofing. Due to the GDPR, it has become increasingly important to have tools and methods to protect the privacy of the users. The H2020 SpeechXRays project...Show More

Evaluation of the H2020 SpeechXRays project Cancelable Face System Under the Framework of ISO/IEC 24745:2011

Mohamed Amine Hmani;Aymen Mtibaa;Dijana Petrovska-Delacrtaz;Claude Bauzou;Iacob Crucianu

Year: 2020 | Conference Paper |

Face Emotion Recognition From Static Image Based on Convolution Neural Networks

M.A. NASRI;M.A. Hmani;A. Mtibaa;D. Petrovska-Delacretaz;M.Ben Slima;A.Ben Hamida

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)
Year: 2020 | Conference Paper |
Cited by: Papers (9)
Human-Machine Interaction systems have not yet reached all the emotional and social capacities. In this paper, we propose a face emotion recognition system from static image based on the Xception convolution neural network architecture and the K-fold-cross-validation strategy. The proposed system was improved using the fine-tuning method. The Xception model pre-trained on ImageNet database for obj...Show More

Face Emotion Recognition From Static Image Based on Convolution Neural Networks

M.A. NASRI;M.A. Hmani;A. Mtibaa;D. Petrovska-Delacretaz;M.Ben Slima;A.Ben Hamida

Year: 2020 | Conference Paper |

Multi-Channel Biometrics for eHealth Combining Acoustic and Machine Vision Analysis of Speech, Lip Movement and Face: a Case Study

Emmanouil G. Spanakis;Dijana Petrovska-Delacrétaz;Claude Bauzou;Iacob Crucianu;Aymen Mtibaa;Mohamed Amine Hmani;Marcel Kockmann;Christian Narr;Elnar Hajiyev;Daniel Takacs;Apostolos Karantanas

2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Year: 2019 | Conference Paper |
The purpose of this work is to present a solution combining user-friendliness and cost-effectiveness use of audio (speech) & visual (video/image) biometrics, for eHealth, able to achieve better accuracy and increase the ability to avoid counterfeiting. This work shows the evaluation results for an eHealth pilot study that tested the security, privacy, usability and cost-effective features of a use...Show More

Multi-Channel Biometrics for eHealth Combining Acoustic and Machine Vision Analysis of Speech, Lip Movement and Face: a Case Study

Emmanouil G. Spanakis;Dijana Petrovska-Delacrétaz;Claude Bauzou;Iacob Crucianu;Aymen Mtibaa;Mohamed Amine Hmani;Marcel Kockmann;Christian Narr;Elnar Hajiyev;Daniel Takacs;Apostolos Karantanas

Year: 2019 | Conference Paper |

State-of-the-art face recognition performance using publicly available software and datasets

Mohamed Amine Hmani;Dijana Petrovska-Delacrétaz

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)
Year: 2018 | Conference Paper |
Cited by: Papers (6)
We are interested in the reproducibility of face recognition systems. By reproducibility we mean: is the scientific community, and are the researchers from different sides, capable of reproducing the last published results by a big company, that has at its disposal huge computational power and huge proprietary databases? With the constant advancements in GPU computation power and availability of o...Show More

State-of-the-art face recognition performance using publicly available software and datasets

Mohamed Amine Hmani;Dijana Petrovska-Delacrétaz

Year: 2018 | Conference Paper |

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