Automated Generation of Transformations to Mitigate Sensor Hardware Migration in ADS
Meriel von Stein, Hongning Wang, Sebastian ElbaumAutonomous 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 data to the old trained network, or the retraining… Read more