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Joseph Azar
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2020 – today
- 2023
- [j6]Hassan N. Noura
, Joseph Azar, Ola Salman, Raphaël Couturier, Kamel Mazouzi:
A deep learning scheme for efficient multimedia IoT data compression. Ad Hoc Networks 138: 102998 (2023) - [j5]Suzan Hajj
, Joseph Azar
, Jacques Bou Abdo
, Jacques Demerjian
, Christophe Guyeux
, Abdallah Makhoul, Dominique Ginhac
:
Cross-Layer Federated Learning for Lightweight IoT Intrusion Detection Systems. Sensors 23(16): 7038 (2023) - [c13]Serge Sandakly, Charbel Salem, Khalil Challita, Shuvalaxmi Dass, Joseph Azar, Jacques Bou Abdo, Jacques Demerjian:
XorshiftH128+: A hybrid random number generator for lightweight IoT. AIBThings 2023: 1-5 - [c12]Mohammad Ali Nemer, Joseph Azar, Abdallah Makhoul, Julien Bourgeois:
Lightweight Feature-based Priority Sampling for Industrial IoT Multivariate Time Series. AICCSA 2023: 1-8 - [c11]Suzan Hajj, Joseph Azar, Jacques Bou Abdo, Jacques Demerjian, Abdallah Makhoul, Dominique Ginhac:
Cross-layer Federated Heterogeneous Ensemble Learning for Lightweight IoT Intrusion Detection System. DSAA 2023: 1-10 - [c10]Jacques M. Bahi, Raphaël Couturier, Joseph Azar, Kevin Kana Nguimfack:
Distributed Training of Deep Neural Networks: Convergence and Case Study. ICONIP (8) 2023: 490-503 - 2022
- [j4]Joseph Azar
, Gaby Bou Tayeh, Abdallah Makhoul, Raphaël Couturier:
Efficient Lossy Compression for IoT Using SZ and Reconstruction with 1D U-Net. Mob. Networks Appl. 27(3): 984-996 (2022) - [c9]Hassan N. Noura, Raphaël Couturier, Joseph Azar, Mohamad Moussa
, Ola Salman:
An Efficient and Robust MIoT Communication Solution using a Deep Learning Approach. IWCMC 2022: 366-371 - [c8]Gaby Bou Tayeh, Joseph Azar, Abdallah Makhoul, Christophe Guyeux, Jacques Demerjian:
On the performance of data-driven approaches for energy efficiency on WiFi and LoRa-based sensors: an experimental study. IWCMC 2022: 883-888 - [c7]Mohammad Ali Nemer, Joseph Azar, Jacques Demerjian, Abdallah Makhoul, Julien Bourgeois:
A Review of Research on Industrial Time Series Classification for Machinery based on Deep Learning. MENACOMM 2022: 89-94 - [c6]Hassan Noura, Joseph Azar, Raphaël Couturier, Ola Salman:
A Novel Lightweight and Robust Source-Channel Coding Solution for MIoT Communication Based on DL Denoising/Super Resolution Model. SITIS 2022: 203-210 - 2021
- [j3]Joseph Azar, Abdallah Makhoul, Raphaël Couturier, Jacques Demerjian:
Deep recurrent neural network-based autoencoder for photoplethysmogram artifacts filtering. Comput. Electr. Eng. 92: 107065 (2021) - 2020
- [b1]Joseph Azar:
Compression de données et apprentissage en profondeur pour les applications de santé IoT basées sur des signaux physiologiques. (Data compression and deep learning for IoT healthcare applications based on physiological signals). University of Burgundy - Franche-Comté, 2020 - [j2]Joseph Azar
, Abdallah Makhoul, Raphaël Couturier, Jacques Demerjian
:
Robust IoT time series classification with data compression and deep learning. Neurocomputing 398: 222-234 (2020) - [c5]Joseph Azar, Abdallah Makhoul, Raphaël Couturier:
Using DenseNet for IoT multivariate time series classification. ISCC 2020: 1-6 - [c4]Gaby Bou Tayeh, Joseph Azar, Abdallah Makhoul, Christophe Guyeux, Jacques Demerjian:
A Wearable LoRa-Based Emergency System for Remote Safety Monitoring. IWCMC 2020: 120-125
2010 – 2019
- 2019
- [j1]Joseph Azar, Abdallah Makhoul, Mahmoud Barhamgi
, Raphaël Couturier
:
An energy efficient IoT data compression approach for edge machine learning. Future Gener. Comput. Syst. 96: 168-175 (2019) - 2018
- [c3]Joseph Azar, Rony Darazi, Carol Habib
, Abdallah Makhoul, Jacques Demerjian
:
Using DWT Lifting Scheme for Lossless Data Compression in Wireless Body Sensor Networks. IWCMC 2018: 1465-1470 - [c2]Joseph Azar, Abdallah Makhoul
, Rony Darazi, Jacques Demerjian
, Raphaël Couturier
:
On the performance of resource-aware compression techniques for vital signs data in wireless body sensor networks. MENACOMM 2018: 1-6 - [c1]Joseph Azar, Carol Habib
, Rony Darazi, Abdallah Makhoul, Jacques Demerjian
:
Using Adaptive Sampling and DWT Lifting Scheme for Efficient Data Reduction in Wireless Body Sensor Networks. WiMob 2018: 1-8
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