9 citations · 34 across the 17 of their papers we have counts for
18 papers
Cross-Lingual Multi-Granularity Framework for Interpretable Parkinson's Disease Diagnosis from Speech
Ilias Tougui, Mehdi Zakroum, Mounir Ghogho
Parkinson's Disease (PD) affects over 10 million people worldwide, with speech impairments in up to 89% of patients. Current speech-based detection systems analyze entire utterance…
Collaborative P4-SDN DDoS Detection and Mitigation with Early-Exit Neural Networks
Ouassim Karrakchou, Alaa Zniber, Anass Sebbar +1
Distributed Denial of Service (DDoS) attacks pose a persistent threat to network security, requiring timely and scalable mitigation strategies. In this paper, we propose a novel co…
Confidence-gated training for efficient early-exit neural networks
Saad Mokssit, Ouassim Karrakchou, Alejandro Mousist +1
Early-exit neural networks reduce inference cost by enabling confident predictions at intermediate layers. However, joint training often leads to gradient interference, with deeper…
Improving Deep Learning-based Respiratory Sound Analysis with Frequency Selection and Attention Mechanism
Nouhaila Fraihi, Ouassim Karrakchou, Mounir Ghogho
Accurate classification of respiratory sounds requires deep learning models that effectively capture fine-grained acoustic features and long-range temporal dependencies. Convolutio…
Robust Planning and Control of Omnidirectional MRAVs for Aerial Communications in Wireless Networks
Giuseppe Silano, Daniel Bonilla Licea, Hajar El Hammouti +2
A new class of Multi-Rotor Aerial Vehicles (MRAVs), known as omnidirectional MRAVs (o-MRAVs), has gained attention for their ability to independently control 3D position and orient…
STRisk: A Socio-Technical Approach to Assess Hacking Breaches Risk
Hicham Hammouchi, Narjisse Nejjari, Ghita Mezzour +2
Data breaches have begun to take on new dimensions and their prediction is becoming of great importance to organizations. Prior work has addressed this issue mainly from a technica…
Reshaping UAV-Enabled Communications with Omnidirectional Multi-Rotor Aerial Vehicles
Daniel Bonilla Licea, Giuseppe Silano, Hajar El Hammouti +2
A new class of Multi-Rotor Aerial Vehicles (MRAVs), known as omnidirectional MRAVs (o-MRAVs), has attracted significant interest in the robotics community. These MRAVs have the uni…
Redefining cystoscopy with ai: bladder cancer diagnosis using an efficient hybrid cnn-transformer model
Meryem Amaouche, Ouassim Karrakchou, Mounir Ghogho +3
Bladder cancer ranks within the top 10 most diagnosed cancers worldwide and is among the most expensive cancers to treat due to the high recurrence rates which require lifetime fol…
Omnidirectional Multi-Rotor Aerial Vehicle Pose Optimization: A Novel Approach to Physical Layer Security
Daniel Bonilla Licea, Giuseppe Silano, Mounir Ghogho +1
The integration of Multi-Rotor Aerial Vehicles (MRAVs) into 5G and 6G networks enhances coverage, connectivity, and congestion management. This fosters communication-aware robotics…
Applications of machine learning and IoT for Outdoor Air Pollution Monitoring and Prediction: A Systematic Literature Review
Ihsane Gryech, Chaimae Assad, Mounir Ghogho +1
According to the World Health Organization (WHO), air pollution kills seven million people every year. Outdoor air pollution is a major environmental health problem affecting low,…
Early Exiting Predictive Coding Neural Networks for Edge AI
Alaa Zniber, Mounir Ghogho, Ouassim Karrakchou +1
The Internet of Things is transforming various fields, with sensors increasingly embedded in wearables, smart buildings, and connected equipment. While deep learning enables valuab…
Dynamic nsNet2: Efficient Deep Noise Suppression with Early Exiting
Riccardo Miccini, Alaa Zniber, Clément Laroche +6
Although deep learning has made strides in the field of deep noise suppression, leveraging deep architectures on resource-constrained devices still proved challenging. Therefore, w…
Multi-Objective Decision Transformers for Offline Reinforcement Learning
Abdelghani Ghanem, Philippe Ciblat, Mounir Ghogho
Offline Reinforcement Learning (RL) is structured to derive policies from static trajectory data without requiring real-time environment interactions. Recent studies have shown the…
EPINN-NSE: Enhanced Physics-Informed Neural Networks for Solving Navier-Stokes Equations
Ayoub Farkane, Mounir Ghogho, Mustapha Oudani +1
Fluid mechanics is a fundamental field in engineering and science. Solving the Navier-Stokes equation (NSE) is critical for understanding the behavior of fluids. However, the NSE i…
When Infodemic Meets Epidemic: a Systematic Literature Review
Chaimae Asaad, Imane Khaouja, Mounir Ghogho +1
Epidemics and outbreaks present arduous challenges requiring both individual and communal efforts. Social media offer significant amounts of data that can be leveraged for bio-surv…
Supervised Contrastive Learning as Multi-Objective Optimization for Fine-Tuning Large Pre-trained Language Models
Youness Moukafih, Mounir Ghogho, Kamel Smaili
Recently, Supervised Contrastive Learning (SCL) has been shown to achieve excellent performance in most classification tasks. In SCL, a neural network is trained to optimize two ob…
KG-NSF: Knowledge Graph Completion with a Negative-Sample-Free Approach
Adil Bahaj, Safae Lhazmir, Mounir Ghogho
Knowledge Graph (KG) completion is an important task that greatly benefits knowledge discovery in many fields (e.g. biomedical research). In recent years, learning KG embeddings to…
Experimental Investigation of Variational Mode Decomposition and Deep Learning for Short-Term Multi-horizon Residential Electric Load Forecasting
Mohamed Aymane Ahajjam, Daniel Bonilla Licea, Mounir Ghogho +1
With the booming growth of advanced digital technologies, it has become possible for users as well as distributors of energy to obtain detailed and timely information about the ele…