Joseph Azar

About Joseph Azar

Joseph Azar, With an exceptional h-index of 9 and a recent h-index of 9 (since 2020), a distinguished researcher at Université de Franche-Comté, specializes in the field of Data Science, E-Health, IoT, Digital Signal Processing, Big Data.

His recent articles reflect a diverse array of research interests and contributions to the field:

Home Automation System with IoT Stack and ChatGPT for People with Reduced Mobility

Distributed Training of Deep Neural Networks: Convergence and Case Study

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

XorshiftH128+: A hybrid random number generator for lightweight IoT

Cross-layer federated learning for lightweight iot intrusion detection systems

A deep learning scheme for efficient multimedia IoT data compression

A review of research on industrial time series classification for machinery based on deep learning

Détection d'anomalies pour les réseaux smart-grids basée sur un autoencodeur LSTM

Joseph Azar Information

University

Position

___

Citations(all)

424

Citations(since 2020)

424

Cited By

118

hIndex(all)

9

hIndex(since 2020)

9

i10Index(all)

8

i10Index(since 2020)

8

Email

University Profile Page

Google Scholar

Joseph Azar Skills & Research Interests

Data Science

E-Health

IoT

Digital Signal Processing

Big Data

Top articles of Joseph Azar

Home Automation System with IoT Stack and ChatGPT for People with Reduced Mobility

2023/12/12

Joseph Azar
Joseph Azar

H-Index: 5

Abdallah Makhoul
Abdallah Makhoul

H-Index: 20

Distributed Training of Deep Neural Networks: Convergence and Case Study

2023/11/20

Joseph Azar
Joseph Azar

H-Index: 5

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

2023/10/9

XorshiftH128+: A hybrid random number generator for lightweight IoT

2023/9/16

Cross-layer federated learning for lightweight iot intrusion detection systems

Sensors

2023/8/9

A deep learning scheme for efficient multimedia IoT data compression

Ad Hoc Networks

2023/1/1

A review of research on industrial time series classification for machinery based on deep learning

2022/12/6

Joseph Azar
Joseph Azar

H-Index: 5

Abdallah Makhoul
Abdallah Makhoul

H-Index: 20

Détection d'anomalies pour les réseaux smart-grids basée sur un autoencodeur LSTM

2022/11/16

Joseph Azar
Joseph Azar

H-Index: 5

Raphaël Couturier
Raphaël Couturier

H-Index: 20

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

2022/10/19

Efficient lossy compression for iot using sz and reconstruction with 1d u-net

Mobile Networks and Applications

2022/6

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

2022/5/30

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

2022/5/30

Deep Learning for IoT-Healthcare Based on Physiological Signals

2022/5/18

Joseph Azar
Joseph Azar

H-Index: 5

Raphaël Couturier
Raphaël Couturier

H-Index: 20

An efficient IoT data compression approach with reconstruction on the edge

2021/7/6

Joseph Azar
Joseph Azar

H-Index: 5

Deep recurrent neural network-based autoencoder for photoplethysmogram artifacts filtering

Computers & Electrical Engineering

2021/6/1

Joseph Azar
Joseph Azar

H-Index: 5

Abdallah Makhoul
Abdallah Makhoul

H-Index: 20

Data compression and deep learning for IoT healthcare applications based on physiological signals

2020/10/9

Joseph Azar
Joseph Azar

H-Index: 5

Compression de données et apprentissage en profondeur pour les applications de santé IoT basées sur des signaux physiologiques

2020/10/9

Joseph Azar
Joseph Azar

H-Index: 5

Robust IoT time series classification with data compression and deep learning

Neurocomputing

2020/7/20

Using DenseNet for IoT multivariate time series classification

2020/7/7

A wearable lora-based emergency system for remote safety monitoring

2020/6/15

See List of Professors in Joseph Azar University(Université de Franche-Comté)

Co-Authors

academic-engine