8 papers
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…
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…
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…
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…