Black-box Safety Analysis and Retraining of DNNs based on Feature Extraction and Clustering. (arXiv:2201.05077v1 [cs.SE])

Deep neural networks (DNNs) have demonstrated superior performance over
classical machine learning to support many features in safety-critical systems.
Although DNNs are now widely used in such systems (e.g., self driving cars),
there is limited progress regarding automated support for functional safety
analysis in DNN-based systems. For example, the identification of root causes
of errors, to enable both risk analysis and DNN retraining, remains an open
problem. In this paper, we propose SAFE, a black-box approach to automatically
characterize the …

analysis arxiv clustering safety