Showing 1–17 of 17 results
/ Date/ Name
Aug 30, 2021The missing link: Developing a safety case for perception components in automated drivingSep 7, 2017An Analysis of ISO 26262: Using Machine Learning Safely in Automotive SoftwareMay 10, 2022A Safety Assurable Human-Inspired Perception ArchitectureAug 5, 2018Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262Jun 25, 2020The Effect of Optimization Methods on the Robustness of Out-of-Distribution Detection ApproachesSep 28, 2022Out-of-Distribution Detection for LiDAR-based 3D Object DetectionFeb 8, 2022If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision ComponentsOct 23, 2019Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer OutputAug 25, 2014Report on the First Workshop On the Globalization of Modeling LanguagesNov 27, 2018Calibrating Uncertainties in Object Localization TaskDec 6, 2018Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis DistanceOct 9, 2019Out-of-distribution Detection in Classifiers via GenerationNov 7, 2019Efficacy of Pixel-Level OOD Detection for Semantic SegmentationAug 17, 2021Robustifying Controller Specifications of Cyber-Physical Systems Against Perceptual UncertaintyApr 27, 2019Analysis of Confident-Classifiers for Out-of-distribution DetectionJul 4, 2019Lifting Datalog-Based Analyses to Software Product LinesMar 3, 2019Towards a Framework to Manage Perceptual Uncertainty for Safe Automated Driving