Katalog der Deutschen Nationalbibliothek
Ergebnis der Suche nach: "Machine Learning"
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Link zu diesem Datensatz | https://d-nb.info/1374506397 |
Titel | Computer Safety, Reliability, and Security : 44th International Conference, SAFECOMP 2025, Stockholm, Sweden, September 10–12, 2025, Proceedings / edited by Barbara Gallina, Martin Törngren, Friedemann Bitsch |
Person(en) |
Gallina, Barbara (Herausgeber) Törngren, Martin (Herausgeber) Bitsch, Friedemann (Herausgeber) |
Organisation(en) | SpringerLink (Online service) (Sonstige) |
Ausgabe | 1st ed. 2026 |
Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
Zeitliche Einordnung | Erscheinungsdatum: 2026 |
Umfang/Format | Online-Ressource, XVIII, 242 p. 98 illus., 78 illus. in color. : online resource. |
Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-032-01240-1 Printed edition:: ISBN: 978-3-032-01242-5 |
Inhalt | -- Safety Arguments/Cases. -- SmartGSN: An Online Tool to Semi-automatically Manage Assurance Cases. -- Principled Safety Assurance Arguments. -- Consensus Building in Level 4 Automated Driving Field Trials through Assurance Cases. -- Data Sets and Dependability Properties. -- Creation and use of a representative dataset for Advanced Persistent Threats detection. -- How Post-Completion Error Leads to Software Faults and Vulnerabilities: Industrial Case Studies. -- Efficient Injury Risk Assessment for Automated Driving Systems Using Subset Simulation. -- Testing and Complex Environments. -- Alignment of SOTIF and Scenario-based Safety Evaluation Framework. -- Managing capability in software dependability testing through generic test rigs. -- Improving Out-of-Distribution Detection via Test-Time Augmentation. -- Methodologies (1) – Safety Design and Risk Assessment. -- Can C-Based ECC Models Leverage High-Level Synthesis? Evaluating Description Variants for Efficient Circuit. -- Hot PASTA: Improved Pragmatics for System-Theoretic Process Analysis. -- ULS: A Unified Likelihood Scale for Cross-Standard Risk Assessment. -- Methodologies (2) – Machine Learning and Large Language Models. -- Large Language Models in Code Co-generation for Safe Autonomous Vehicles. .-Balancing the Risks and Benefits of using Large Language Models to Support Assurance Case Development. -- Exploring the Potential of LSTM On Emulating Multiple-bit Fault Injection in SRAM-FPGA |
Persistent Identifier |
URN: urn:nbn:de:101:1-2508220412108.604578457624 DOI: 10.1007/978-3-032-01241-8 |
URL | https://doi.org/10.1007/978-3-032-01241-8 |
ISBN/Einband/Preis | 978-3-032-01241-8 |
Sprache(n) | Englisch (eng) |
Beziehungen | Lecture Notes in Computer Science ; 15954 |
DDC-Notation | 005.8 (maschinell ermittelte DDC-Kurznotation) |
Sachgruppe(n) | 004 Informatik |
Online-Zugriff | Archivobjekt öffnen |
