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Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving
Practical learning-based autonomous driving models must be capable of generalizing learned behaviors from simulated to real domains, and from training data to unseen domains with unusual image properties.
Enhanced Transfer Learning for Autonomous Driving with Systematic Accident Simulation
Simulation data can be utilized to extend real-world driving data in order to cover edge cases, such as vehicle accidents.
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