Khalid El Makkaoui

A lightweight deep learning model for real-time in-vehicle driver distraction detection with low-latency inference

Siham Essahraui, Chaymae Rami, Khalid El Makkaoui, Ibrahim Ouahbi

A Tiny Vision-Based Model for Real-Time Student Attention Detection in Online Classes

Chaymae Yahyati, Ismail Lamaakal, Yassine Maleh, Khalid El Makkaoui, Ibrahim Ouahbi

Online and blended classrooms widen access but remove the in-person cues instructors use to gauge attention. Prior work typically relies on heavy, cloud-bound or multimodal models that are hard to deploy on commodity laptops, treats attention as an unordered label without calibra…Read more

Explainable Kolmogorov–Arnold Networks for Zero-Shot Human Activity Recognition on TinyML Edge Devices

Ismail Lamaakal, Chaymae Yahyati, Yassine Maleh, Khalid El Makkaoui, Ibrahim Ouahbi

Human Activity Recognition (HAR) on wearable and IoT devices must jointly satisfy four requirements: high accuracy, the ability to recognize previously unseen activities, strict memory and latency constraints, and interpretable decisions. In this work, we address all four by intr…Read more

Real-Time Driver Drowsiness Detection Using Facial Analysis and Machine Learning Techniques

Siham Essahraui, Ismail Lamaakal, Ikhlas El Hamly, Yassine Maleh, Ibrahim Ouahbi, Khalid El Makkaoui, et al.

Drowsy driving poses a significant challenge to road safety worldwide, contributing to thousands of accidents and fatalities annually. Despite advancements in driver drowsiness detection (DDD) systems, many existing methods face limitations such as intrusiveness and delayed react…Read more