Joseph Azar

According to our database, Joseph Azar authored at least 20 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Cross-Layer Federated Learning for Lightweight IoT Intrusion Detection Systems.

Suzan Hajj, Joseph Azar, Jacques Bou Abdo, Jacques Demerjian, Christophe Guyeux, Abdallah Makhoul, Dominique Ginhac

Sensors, August, 2023

A deep learning scheme for efficient multimedia IoT data compression.

Hassan N. Noura, Joseph Azar, Ola Salman, Raphaël Couturier, Kamel Mazouzi

Ad Hoc Networks, 2023

Distributed Training of Deep Neural Networks: Convergence and Case Study.

Jacques M. Bahi, Raphaël Couturier, Joseph Azar, Kevin Kana Nguimfack

Proceedings of the Neural Information Processing - 30th International Conference, 2023

Cross-layer Federated Heterogeneous Ensemble Learning for Lightweight IoT Intrusion Detection System.

Suzan Hajj, Joseph Azar, Jacques Bou Abdo, Jacques Demerjian, Abdallah Makhoul, Dominique Ginhac

Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

Lightweight Feature-based Priority Sampling for Industrial IoT Multivariate Time Series.

Mohammad Ali Nemer, Joseph Azar, Abdallah Makhoul, Julien Bourgeois

Proceedings of the 20th ACS/IEEE International Conference on Computer Systems and Applications, 2023

XorshiftH128+: A hybrid random number generator for lightweight IoT.

Serge Sandakly, Charbel Salem, Khalil Challita, Shuvalaxmi Dass, Joseph Azar, Jacques Bou Abdo, Jacques Demerjian

Proceedings of the IEEE International Conference on Artificial Intelligence, 2023

2022

Efficient Lossy Compression for IoT Using SZ and Reconstruction with 1D U-Net.

Joseph Azar, Gaby Bou Tayeh, Abdallah Makhoul, Raphaël Couturier

Mob. Networks Appl., 2022

A Novel Lightweight and Robust Source-Channel Coding Solution for MIoT Communication Based on DL Denoising/Super Resolution Model.

Hassan Noura, Joseph Azar, Raphaël Couturier, Ola Salman

Proceedings of the 16th International Conference on Signal-Image Technology & Internet-Based Systems, 2022

A Review of Research on Industrial Time Series Classification for Machinery based on Deep Learning.

Mohammad Ali Nemer, Joseph Azar, Jacques Demerjian, Abdallah Makhoul, Julien Bourgeois

Proceedings of the 4th IEEE Middle East and North Africa COMMunications Conference, 2022

On the performance of data-driven approaches for energy efficiency on WiFi and LoRa-based sensors: an experimental study.

Gaby Bou Tayeh, Joseph Azar, Abdallah Makhoul, Christophe Guyeux, Jacques Demerjian

Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022

An Efficient and Robust MIoT Communication Solution using a Deep Learning Approach.

Hassan N. Noura, Raphaël Couturier, Joseph Azar, Mohamad Moussa, Ola Salman

Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022

2021

Deep recurrent neural network-based autoencoder for photoplethysmogram artifacts filtering.

Joseph Azar, Abdallah Makhoul, Raphaël Couturier, Jacques Demerjian

Comput. Electr. Eng., 2021

2020

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).

Joseph Azar

PhD thesis, 2020

Robust IoT time series classification with data compression and deep learning.

Joseph Azar, Abdallah Makhoul, Raphaël Couturier, Jacques Demerjian

Neurocomputing, 2020

A Wearable LoRa-Based Emergency System for Remote Safety Monitoring.

Gaby Bou Tayeh, Joseph Azar, Abdallah Makhoul, Christophe Guyeux, Jacques Demerjian

Proceedings of the 16th International Wireless Communications and Mobile Computing Conference, 2020

Using DenseNet for IoT multivariate time series classification.

Joseph Azar, Abdallah Makhoul, Raphaël Couturier

Proceedings of the IEEE Symposium on Computers and Communications, 2020

2019

An energy efficient IoT data compression approach for edge machine learning.

Joseph Azar, Abdallah Makhoul, Mahmoud Barhamgi, Raphaël Couturier

Future Gener. Comput. Syst., 2019

2018

Using Adaptive Sampling and DWT Lifting Scheme for Efficient Data Reduction in Wireless Body Sensor Networks.

Joseph Azar, Carol Habib, Rony Darazi, Abdallah Makhoul, Jacques Demerjian

Proceedings of the 14th International Conference on Wireless and Mobile Computing, 2018

On the performance of resource-aware compression techniques for vital signs data in wireless body sensor networks.

Joseph Azar, Abdallah Makhoul, Rony Darazi, Jacques Demerjian, Raphaël Couturier

Proceedings of the IEEE Middle East and North Africa Communications Conference, 2018

Using DWT Lifting Scheme for Lossless Data Compression in Wireless Body Sensor Networks.

Joseph Azar, Rony Darazi, Carol Habib, Abdallah Makhoul, Jacques Demerjian

Proceedings of the 14th International Wireless Communications & Mobile Computing Conference, 2018