4 citations · 7 across the 10 of their papers we have counts for
10 papers
Enhancing Early Alzheimer Disease Detection through Big Data and Ensemble Few-Shot Learning
Safa Ben Atitallah, Maha Driss, Wadii Boulila +1
Alzheimer disease is a severe brain disorder that causes harm in various brain areas and leads to memory damage. The limited availability of labeled medical data poses a significan…
SOH-KLSTM: A Hybrid Kolmogorov-Arnold Network and LSTM Model for Enhanced Lithium-Ion Battery Health Monitoring
Imen Jarraya, Safa Ben Atitallah, Fatimah Alahmeda +4
Accurate and reliable State Of Health (SOH) estimation for Lithium (Li) batteries is critical to ensure the longevity, safety, and optimal performance of applications like electric…
GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Matryoshka Representation Learning and Hybrid Loss Training
Omer Nacar, Anis Koubaa, Serry Sibaee +3
Semantic textual similarity (STS) is a critical task in natural language processing (NLP), enabling applications in retrieval, clustering, and understanding semantic relationships…
Optimizing Retrieval-Augmented Generation: Analysis of Hyperparameter Impact on Performance and Efficiency
Adel Ammar, Anis Koubaa, Omer Nacar +1
Large language models achieve high task performance yet often hallucinate or rely on outdated knowledge. Retrieval-augmented generation (RAG) addresses these gaps by coupling gener…
Exploring Graph Mamba: A Comprehensive Survey on State-Space Models for Graph Learning
Safa Ben Atitallah, Chaima Ben Rabah, Maha Driss +2
Graph Mamba, a powerful graph embedding technique, has emerged as a cornerstone in various domains, including bioinformatics, social networks, and recommendation systems. This surv…
Enhancing Internet of Things Security throughSelf-Supervised Graph Neural Networks
Safa Ben Atitallah, Maha Driss, Wadii Boulila +1
With the rapid rise of the Internet of Things (IoT), ensuring the security of IoT devices has become essential. One of the primary challenges in this field is that new types of att…
Self-Supervised Learning for Graph-Structured Data in Healthcare Applications: A Comprehensive Review
Safa Ben Atitallah, Chaima Ben Rabah, Maha Driss +2
The abundance of complex and interconnected healthcare data offers numerous opportunities to improve prediction, diagnosis, and treatment. Graph-structured data, which includes ent…
Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning
Safa Ben Atitallah, Maha Driss, Wadii Boulila +1
The Internet of Things (IoT) has been introduced as a breakthrough technology that integrates intelligence into everyday objects, enabling high levels of connectivity between them.…
An Effective Weight Initialization Method for Deep Learning: Application to Satellite Image Classification
Wadii Boulila, Eman Alshanqiti, Ayyub Alzahem +2
The growing interest in satellite imagery has triggered the need for efficient mechanisms to extract valuable information from these vast data sources, providing deeper insights. E…
Feature Fusion for Improved Classification: Combining Dempster-Shafer Theory and Multiple CNN Architectures
Ayyub Alzahem, Wadii Boulila, Maha Driss +1
Addressing uncertainty in Deep Learning (DL) is essential, as it enables the development of models that can make reliable predictions and informed decisions in complex, real-world…