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Author

A. Sahbani

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Review Open access 2026

How Emergent Architectures Solve the Bird’s Eyes View Shortcomings: A Systematic Review

Autonomous driving requires robust, accurate and real-time environmental perception. Although cameras, LiDAR, and radar provide complementary sensing capabilities, individual modalities remain vulnerable to limitations such as depth ambiguity, point-cloud sparsity, adverse weather, and restricted angular resolution. Mu...

A. Sahbani, Rihem Sebai, T. Bejaoui et al. · 0 citations
Sep 2026

A Multi-Paradigm AI Framework for Explainable and Proactive Battery State-of-Health Estimation in Electric Vehicles

The State of Health (SOH) estimation of the lithium-ion batteries is essential for safe and efficient electric vehicle operation. Existing techniques often used black-box models, needing interpretability and the interaction of the user. This paper represents a multi-paradigm AI framework that combines deep learning, ne...

Ghada Toumi, A. Sahbani, H. Mahersia · 0 citations
Conference Jul 2026

Robust Multi-Sensor Fusion Architecture Tested on CARLA Sim

This paper presents a multi-sensor fusion architecture with camera data segmentation. Robust perception is a fundamental prerequisite for the safety of autonomous vehicles, particularly in dynamic environments and varying weather conditions. Multi-sensor fusion approaches, integrating camera and LiDAR data, have emerge...

Rihem Sebai, A. Sahbani, T. Bejaoui · 0 citations

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