Research papers · Posted 2019.09.30 · Preprint
Towards Robust Direct Perception Networks for Automated Driving
Towards Robust Direct Perception Networks for Automated Driving
Overview
The approach incorporates tolerated output error into regression-network loss and robustness criteria. Symbolic propagation of bounded intermediate-layer perturbations supports training, demonstrated on direct perception of the ego-lane center in images.
Author-supplied source information
Author-supplied information on arXiv.
Preprint. Work in progress
Version: v1