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Improving the Validation of Automotive Self-Learning Systems through the Synergy of Scenario-Based Testing and Metamorphic Relations.

, , , and . BDCAT, page 02:1-02:7. ACM, (2023)

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Isolation Forest for Anomaly Detection in Raw Vehicle Sensor Data., and . VEHITS, page 411-416. SciTePress, (2018)Digitalization in automotive and industrial systems., , , , and . DATE, page 1203-1204. IEEE, (2018)Estimating the Uniqueness of Test Scenarios derived from Recorded Real-World-Driving-Data using Autoencoders., , , , , and . Intelligent Vehicles Symposium, page 1860-1866. IEEE, (2018)Classification of Automotive Electric/Electronic Features and the Consequent Hierarchization of the Logical System Architecture - From Functional Chains to Functional Networks., , and . SMARTGREENS/VEHITS (Selected Papers), volume 921 of Communications in Computer and Information Science, page 229-255. Springer, (2017)Cloud-based Design and Virtual Prototyping Environment for Embedded Systems., , , , , and . Int. J. Online Eng., 12 (9): 52-60 (2016)A multi-objective optimization approach for analysing and architecting system of systems., , , and . SysCon, page 1-8. IEEE, (2018)Model-based validation and testing of industry 4.0 plants., , , , and . SysCon, page 1-8. IEEE, (2018)Lifecycle Management of Automotive Safety-Critical Over the Air Updates: A Systems Approach., , , , , and . IEEE Access, (2022)Context-Aware Security for Vehicles and Fleets: A Survey., , and . IEEE Access, (2021)EfficientPPS: Part-aware Panoptic Segmentation of Transparent Objects for Robotic Manipulation., , , , , , and . CoRR, (2023)