194 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of DubaiAE9 papers
- University of Sciences and Technology Houari BoumedieneDZ9 papers
- American University of SharjahAE6 papers
- Queen's University BelfastGB6 papers
- University of LiverpoolGB5 papers
- University of BahrainBH4 papers
- University of SharjahAE4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Institut d'Astrophysique de ParisFR3 papers
- London Metropolitan UniversityGB3 papers
- Northwest African American MuseumUS3 papers
- Qatar UniversityQA3 papers
45 papers
Reinforcement learning for hardware acceleration and system-level optimization on FPGA and integrated-circuit platforms: A survey
Hamza Kheddar
Reinforcement learning (RL) enables adaptive and autonomous decision-making in embedded, edge, and heterogeneous computing systems. Field-programmable gate arrays (FPGAs) and integ…
BreathAI: Transfer Learning-Based Thermal Imaging for Automated Breathing Pattern Recognition
Hamza Kheddar, Yassine Himeur, Abbes Amira
This study presents an Adaptive Transfer Learning and Thresholding-based Deep Learning Model (ATL-TDLM) for automated breathing pattern recognition using thermal imaging. Unlike co…
Hybrid ResNet-1D-BiGRU with Multi-Head Attention for Cyberattack Detection in Industrial IoT Environments
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari
This study introduces a hybrid deep learning model for intrusion detection in Industrial IoT (IIoT) systems, combining ResNet-1D, BiGRU, and Multi-Head Attention (MHA) for effectiv…
SE-Enhanced ViT and BiLSTM-Based Intrusion Detection for Secure IIoT and IoMT Environments
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari +2
With the rapid growth of interconnected devices in Industrial and Medical Internet of Things (IIoT and MIoT) ecosystems, ensuring timely and accurate detection of cyber threats has…
Structure of non-global logarithms with Cambridge/Aachen clustering
K. Khelifa-Kerfa
We determine the structure of both Abelian and non-Abelian non-global logarithms up to four loops for processes in perturbative QCD, where final-state jets are defined usi…
A Robust Cross-Domain IDS using BiGRU-LSTM-Attention for Medical and Industrial IoT Security
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari +1
The increased Internet of Medical Things IoMT and the Industrial Internet of Things IIoT interconnectivity has introduced complex cybersecurity challenges, exposing sensitive data,…
Recent Advances in Transformer and Large Language Models for UAV Applications
Hamza Kheddar, Yassine Habchi, Mohamed Chahine Ghanem +2
The rapid advancement of Transformer-based models has reshaped the landscape of uncrewed aerial vehicle (UAV) systems by enhancing perception, decision-making, and autonomy. This r…
Hierarchical Graph Neural Network for Compressed Speech Steganalysis
Mustapha Hemis, Hamza Kheddar, Mohamed Chahine Ghanem +1
Steganalysis methods based on deep learning (DL) often struggle with computational complexity and challenges in generalizing across different datasets. Incorporating a graph neural…
Multilinear subspace learning for person re-identification based fusion of high order tensor features
Ammar Chouchane, Mohcene Bessaoudi, Hamza Kheddar +3
Video surveillance image analysis and processing is a challenging field in computer vision, with one of its most difficult tasks being Person Re-Identification (PRe-ID). PRe-ID aim…
Transfer Learning-Based Deep Residual Learning for Speech Recognition in Clean and Noisy Environments
Noussaiba Djeffal, Djamel Addou, Hamza Kheddar +1
Addressing the detrimental impact of non-stationary environmental noise on automatic speech recognition (ASR) has been a persistent and significant research focus. Despite advancem…
Enhancing Cochlear Implant Signal Coding with Scaled Dot-Product Attention
Billel Essaid, Hamza Kheddar, Noureddine Batel
Cochlear implants (CIs) play a vital role in restoring hearing for individuals with severe to profound sensorineural hearing loss by directly stimulating the auditory nerve with el…
Improving Pretrained YAMNet for Enhanced Speech Command Detection via Transfer Learning
Sidahmed Lachenani, Hamza Kheddar, Mohamed Ouldzmirli
This work addresses the need for enhanced accuracy and efficiency in speech command recognition systems, a critical component for improving user interaction in various smart applic…
Advanced Deep Learning and Large Language Models: Comprehensive Insights for Cancer Detection
Yassine Habchi, Hamza Kheddar, Yassine Himeur +4
The rapid advancement of deep learning (DL) has transformed healthcare, particularly in cancer detection and diagnosis. DL surpasses traditional machine learning and human accuracy…
Adaptive Cyber-Attack Detection in IIoT Using Attention-Based LSTM-CNN Models
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari
The rapid expansion of the industrial Internet of things (IIoT) has introduced new challenges in securing critical infrastructures against sophisticated cyberthreats. This study pr…
Automatic Speech Recognition with BERT and CTC Transformers: A Review
Noussaiba Djeffal, Hamza Kheddar, Djamel Addou +2
This review paper provides a comprehensive analysis of recent advances in automatic speech recognition (ASR) with bidirectional encoder representations from transformers BERT and c…
Advanced Persistent Threats (APT) Attribution Using Deep Reinforcement Learning
Animesh Singh Basnet, Mohamed Chahine Ghanem, Dipo Dunsin +1
The development of the DRL model for malware attribution involved extensive research, iterative coding, and numerous adjustments based on the insights gathered from predecessor mod…
Transformers and Large Language Models for Efficient Intrusion Detection Systems: A Comprehensive Survey
Hamza Kheddar
With significant advancements in Transformers LLMs, NLP has extended its reach into many research fields due to its enhanced capabilities in text generation and user interaction. O…
Deep Reinforcement Learning for Intrusion Detection in IoT: A Survey
Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari
The rise of new complex attacks scenarios in Internet of things (IoT) environments necessitate more advanced and intelligent cyber defense techniques such as various Intrusion Dete…
Automatic Speech Recognition using Advanced Deep Learning Approaches: A survey
Hamza Kheddar, Mustapha Hemis, Yassine Himeur
Recent advancements in deep learning (DL) have posed a significant challenge for automatic speech recognition (ASR). ASR relies on extensive training datasets, including confidenti…
Artificial Intelligence for Cochlear Implants: Review of Strategies, Challenges, and Perspectives
Billel Essaid, Hamza Kheddar, Noureddine Batel +2
Automatic speech recognition (ASR) plays a pivotal role in our daily lives, offering utility not only for interacting with machines but also for facilitating communication for indi…
Machine Learning and Transformers for Thyroid Carcinoma Diagnosis: A Review
Yassine Habchi, Hamza Kheddar, Yassine Himeur +1
The growing interest in developing smart diagnostic systems to help medical experts process extensive data for treating incurable diseases has been notable. In particular, the chal…
Image and Point-cloud Classification for Jet Analysis in High-Energy Physics: A survey
Hamza Kheddar, Yassine Himeur, Abbes Amira +1
Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and…
Deep Learning for Steganalysis of Diverse Data Types: A review of methods, taxonomy, challenges and future directions
Hamza Kheddar, Mustapha Hemis, Yassine Himeur +2
Steganography and steganalysis are two interrelated aspects of the field of information security. Steganography seeks to conceal communications, whereas steganalysis is aimed to ei…
Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization
Hamza Kheddar, Yassine Himeur, Somaya Al-Maadeed +2
Automatic speech recognition (ASR) has recently become an important challenge when using deep learning (DL). It requires large-scale training datasets and high computational and st…