8 papers
Physically-Constrained Harmonic Separation for Robust Heart and Respiratory Rate Estimation from Wrist Photoplethysmography
Nouhaila Fraihi, Ouassim Karrakchou, Mounir Ghogho
Wrist-worn photoplethysmography (PPG) enables continuous monitoring of cardiopulmonary physiology, but reliable heart rate (HR) and respiratory rate (RR) estimation in free-living…
Adaptive Band Selection for Hyperspectral Classification with Spatially Disjoint Evaluation
Ikram El-Hajri, Ouassim Karrakchou, Alejandro Mousist
Hyperspectral band selection methods based on differentiable selectors can be sensitive to initialization and to extracting a final discrete subset, while prescribed band counts li…
Balancing Stability and Plasticity in Sequentially Trained Early-Exiting Neural Networks
Alaa Zniber, Ouassim Karrakchou, Mounir Ghogho
Early-exiting neural networks enable adaptive inference by allowing inputs to exit at intermediate classifiers, reducing computation for easy samples while maintaining high accurac…
Hardware-Algorithm Co-Optimization of Early-Exit Neural Networks for Multi-Core Edge Accelerators
Alaa Zniber, Arne Symons, Ouassim Karrakchou +2
The deployment of Early-Exiting Neural Networks (EENNs) on edge accelerators requires optimizing not only the network architecture but also its hardware deployment. Exit configurat…
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…
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…