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A Driving Scenario Representation for Scalable Real-Data Analytics with Neural Networks.

, , , , and . IV, page 2215-2222. IEEE, (2019)

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A Driving Scenario Representation for Scalable Real-Data Analytics with Neural Networks., , , , and . IV, page 2215-2222. IEEE, (2019)Training and Validation Methodology for Range Estimation Algorithms., , , , , and . VEHITS, page 434-443. SciTePress, (2019)Model based scenario specification for development and test of automated driving functions., , and . Intelligent Vehicles Symposium, page 1149-1155. IEEE, (2016)Identifikation von Fahrszenarien während einer virtuellen Testfahrt., , , and . GI-Jahrestagung, volume P-275 of LNI, page 1511-1516. GI, (2017)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)Rapid safety evaluation of hardware architectural designs compliant with ISO 26262., , , and . RSP, page 66-72. IEEE, (2013)Integrating Static Code Analysis Toolchains., , , , , , and . COMPSAC (1), page 523-528. IEEE, (2019)Logical Scenario Derivation by Clustering Dynamic-Length-Segments Extracted from Real-World-Driving-Data., , , , and . VEHITS, page 458-467. SciTePress, (2019)Test scenario selection for system-level verification and validation of geolocation-dependent automotive control systems., , , , and . ICE/ITMC, page 203-210. IEEE, (2017)