2024
Automated Generation of Transformations to Mitigate Sensor Hardware Migration in ADS
RA-L 2024
Autonomous driving systems (ADSs) rely on massive amounts of sensed data to train their underlying deep neural networks (DNNs). Common sensor hardware migrations can render an existing DNN-dependent pipeline inadequate. This necessitates the development of bespoke transformations to adapt new sensor