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Knowledge Graph-Based Methods for Automated Driving
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Knowledge Graph-based Methods for Automated Driving
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Knowledge Graph-based Methods for Automated Driving
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Add to basketCondition: New. Systematically covers knowledge graphs for automated driving processesIncludes real-life case studies, facilitating an understanding of current challengesAnalyzes the impact of various technological aspects related to automation ac.
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Knowledge Graph-Based Methods for Automated Driving
Language: English
Published by Elsevier - Health Sciences Division Mai 2025, 2025
ISBN 10: 0443300402 ISBN 13: 9780443300400
Taschenbuch. Condition: Neu. Neuware - The global race to develop and deploy automated vehicles is still hindered by significant challenges, with the related complexities requiring multidisciplinary research approaches. Knowledge Graph-Based Methods for Automated Driving offers sought-after, specialized know-how for a wide range of readers both in academia and industry on the use of graphs as knowledge representation techniques which, compared to other relational models, provide a number of advantages for data-driven applications like automated driving tasks. The machine learning pipeline presented in this volume incorporates a variety of auxiliary information, including logic rules, ontology-informed workflows, simulation outcomes, differential equations, and human input, with the resulting operational framework being more reliable, secure, efficient as well as sustainable. Case studies and other practical discussions exemplify these methods' promising and exciting prospects for the maturation of scalable solutions with potential to transform transport and logistics worldwide.
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Knowledge Graph-Based Methods for Automated Driving (Paperback)
Language: English
Published by Elsevier - Health Sciences Division, Philadelphia, 2025
ISBN 10: 0443300402 ISBN 13: 9780443300400
Paperback. Condition: new. Paperback. The global race to develop and deploy automated vehicles is still hindered by significant challenges, with the related complexities requiring multidisciplinary research approaches.Knowledge Graph-Based Methods for Automated Driving offers sought-after, specialized know-how for a wide range of readers both in academia and industry on the use of graphs as knowledge representation techniques which, compared to other relational models, provide a number of advantages for data-driven applications like automated driving tasks. The machine learning pipeline presented in this volume incorporates a variety of auxiliary information, including logic rules, ontology-informed workflows, simulation outcomes, differential equations, and human input, with the resulting operational framework being more reliable, secure, efficient as well as sustainable.Case studies and other practical discussions exemplify these methods promising and exciting prospects for the maturation of scalable solutions with potential to transform transport and logistics worldwide. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Knowledge Graph-Based Methods for Automated Driving
Language: English
Published by Elsevier - Health Sciences Division, 2025
ISBN 10: 0443300402 ISBN 13: 9780443300400
Condition: new. Questo è un articolo print on demand.
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Knowledge Graph-based Methods for Automated Driving
Language: English
Published by Elsevier Science Ltd, 2025
ISBN 10: 0443300402 ISBN 13: 9780443300400
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Add to basketPaperback. Condition: Brand New. 400 pages. 9.00x6.00x9.02 inches. In Stock. This item is printed on demand.
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Knowledge Graph-Based Methods for Automated Driving (Paperback)
Language: English
Published by Elsevier - Health Sciences Division, Philadelphia, 2025
ISBN 10: 0443300402 ISBN 13: 9780443300400
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Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: new. Paperback. The global race to develop and deploy automated vehicles is still hindered by significant challenges, with the related complexities requiring multidisciplinary research approaches.Knowledge Graph-Based Methods for Automated Driving offers sought-after, specialized know-how for a wide range of readers both in academia and industry on the use of graphs as knowledge representation techniques which, compared to other relational models, provide a number of advantages for data-driven applications like automated driving tasks. The machine learning pipeline presented in this volume incorporates a variety of auxiliary information, including logic rules, ontology-informed workflows, simulation outcomes, differential equations, and human input, with the resulting operational framework being more reliable, secure, efficient as well as sustainable.Case studies and other practical discussions exemplify these methods promising and exciting prospects for the maturation of scalable solutions with potential to transform transport and logistics worldwide. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
