A transformer-based 3D object detector for autonomous driving is extended with attention-derived saliency maps, perturbation-validated faithfulness checks, uncertainty calibration, and robustness training, then deployed on a prototype vehicle with a real-time XAI monitoring interface.
Bayesod: A bayesian approach for uncertainty estimation in deep object detectors
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Towards Trustworthy and Explainable AI for Perception Models: From Concept to Prototype Vehicle Deployment
A transformer-based 3D object detector for autonomous driving is extended with attention-derived saliency maps, perturbation-validated faithfulness checks, uncertainty calibration, and robustness training, then deployed on a prototype vehicle with a real-time XAI monitoring interface.