4 papers
Towards Safety Verification of Direct Perception Neural Networks
Chih-Hong Cheng, Chung-Hao Huang, Thomas Brunner +1
We study the problem of safety verification of direct perception neural networks, where camera images are used as inputs to produce high-level features for autonomous vehicles to m…
nn-dependability-kit: Engineering Neural Networks for Safety-Critical Autonomous Driving Systems
Chih-Hong Cheng, Chung-Hao Huang, Georg Nührenberg
Can engineering neural networks be approached in a disciplined way similar to how engineers build software for civil aircraft? We present nn-dependability-kit, an open-source toolb…
Towards Dependability Metrics for Neural Networks
Chih-Hong Cheng, Georg Nührenberg, Chung-Hao Huang +2
Artificial neural networks (NN) are instrumental in realizing highly-automated driving functionality. An overarching challenge is to identify best safety engineering practices for…
Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems
Chih-Hong Cheng, Chung-Hao Huang, Hirotoshi Yasuoka
Systematically testing models learned from neural networks remains a crucial unsolved barrier to successfully justify safety for autonomous vehicles engineered using data-driven ap…