Author

Siham Essahraui

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Open access Oct 2026

Robustness Evaluation of Lightweight YOLO Detectors for Traffic Monitoring Under Visual Corruptions and Adversarial Attacks

Reliable traffic-object detection remains challenging when visual conditions degrade or when the detector is exposed to adversarial perturbations. This study investigates these robustness challenges through a systematic evaluation of lightweight YOLO detectors for intelligent traffic monitoring. Several nano-scale vari...

Chaymae Rami, Siham Essahraui, Ibrahim Ouahbi et al. · Journal of Cybersecurity and... · 0 citations

Review Open access Jul 2026

Text-to-Image Generation via Deep Learning: A Comprehensive Review of Models, Architectures, and Future Directions

The paradigms of the generative adversarial networks (GANs), variational autoencoders (VAEs), transformer-based designs, and diffusion models, with the last one representing the state of the art in image generation models are discussed.

Abdussalam Elhanashi, Siham Essahraui, Qinghe Zheng et al. · Applied Sciences · 0 citations

Open access Jul 2026

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

Experiments on the State Farm Distracted Driver Detection dataset show that MobileNetV3-Large provides the best trade-off among the evaluated lightweight models, demonstrating a practical balance between unseen-driver generalization, interpretability, and real-time embedded inference.

Siham Essahraui, Chaymae Rami, Khalid El Makkaoui et al. · Scientific Reports · 0 citations