Houben sebastian (26 risultati)
Deep Neural Networks and Data for Automated Driving : Robustness, Uncertainty Quantification, and Insights Towards Safety
Fingscheidt, Tim (EDT); Gottschalk, Hanno (EDT); Houben, Sebastian (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Deep Neural Networks and Data for Automated Driving : Robustness, Uncertainty Quantification, and Insights Towards Safety
Fingscheidt, Tim (EDT); Gottschalk, Hanno (EDT); Houben, Sebastian (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: California Books, Miami, FL, U.S.A.California Books
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Deep Neural Networks and Data for Automated Driving : Robustness, Uncertainty Quantification, and Insights Towards Safety
Fingscheidt, Tim (EDT); Gottschalk, Hanno (EDT); Houben, Sebastian (EDT)
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
Deep Neural Networks and Data for Automated Driving : Robustness, Uncertainty Quantification, and Insights Towards Safety
Fingscheidt, Tim (EDT); Gottschalk, Hanno (EDT); Houben, Sebastian (EDT)
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Condizione: As New. Unread book in perfect condition.
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condizione: New.
Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty Quantification, and Insights Towards Safety
Fingscheidt, Tim (Editor)/ Gottschalk, Hanno (Editor)/ Houben, Sebastian (Editor)
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 445 pages. 9.25x6.10x9.21 inches. In Stock.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural networks, facing many challen…ges. How much data do we need for training and testing How to use synthetic data to save labeling costs for training How do we increase robustness and decrease memory usage For inevitably poor conditions: How do we know that the network is uncertain about its decisions Can we understand a bit more about what actually happens inside neural networks This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.
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Da: Buchpark, Trebbin, GermaniaBuchpark
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Condizione: Gut. Zustand: Gut | Seiten: 448 | Sprache: Englisch | Produktart: Bücher | This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural networks, facing many cha…llenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety?This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and,last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 58,56
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. Ho…w much data do we need for training and testing How to use synthetic data to save labeling costs for training How do we increase robustness and decrease memory usage For inevitably poor conditions: How do we know that the network is uncertain about its decisions Can we understand a bit more about what actually happens inside neural networks This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and,last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.
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Da: Buchpark, Trebbin, GermaniaBuchpark
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EUR 26,48
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Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 448 | Sprache: Englisch | Produktart: Bücher | This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural network…s, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety?This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.
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- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural networks, fac…ing many challenges. How much data do we need for training and testing How to use synthetic data to save labeling costs for training How do we increase robustness and decrease memory usage For inevitably poor conditions: How do we know that the network is uncertain about its decisions Can we understand a bit more about what actually happens inside neural networks This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above. 448 pp. Englisch.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural networks, facing man…y challenges. How much data do we need for training and testing How to use synthetic data to save labeling costs for training How do we increase robustness and decrease memory usage For inevitably poor conditions: How do we know that the network is uncertain about its decisions Can we understand a bit more about what actually happens inside neural networks This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above. 448 pp. Englisch.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|University of Wuppertal|Springer, 2022
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Da: moluna, Greven, Germaniamoluna
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EUR 39,60
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neura…l networks, facing many challen.
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- Print on Demand
Da: moluna, Greven, Germaniamoluna
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EUR 48,37
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the latest developments from industry and research on automated driving and artificial intelligenceProvides in introduction to current knowledge in neural networks and AIProvides a basis for future research…and a guide for practiti.
Lingua: Inglese
Editore: Springer International Publishing, Springer Nature Switzerland Jul 2022, 2022
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 42,79
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural networks, facing…many challenges. How much data do we need for training and testing How to use synthetic data to save labeling costs for training How do we increase robustness and decrease memory usage For inevitably poor conditions: How do we know that the network is uncertain about its decisions Can we understand a bit more about what actually happens inside neural networks This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 448 pp. Englisch.
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Deep Neural Networks and Data for Automated Driving | Robustness, Uncertainty Quantification, and Insights Towards Safety | Jeonghoon Mo | Taschenbuch | X | Englisch | 2022 | Springer Nature Switzerland | EAN 9783031012358 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17,… 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing Jun 2022, 2022
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,49
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural networks, facing many ch…allenges. How much data do we need for training and testing How to use synthetic data to save labeling costs for training How do we increase robustness and decrease memory usage For inevitably poor conditions: How do we know that the network is uncertain about its decisions Can we understand a bit more about what actually happens inside neural networks This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and,last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 448 pp. Englisch.
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Da: preigu, Osnabrück, Germaniapreigu
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Buch. Condizione: Neu. Deep Neural Networks and Data for Automated Driving | Robustness, Uncertainty Quantification, and Insights Towards Safety | Tim Fingscheidt (u. a.) | Buch | xviii | Englisch | 2022 | Springer | EAN 9783031012327 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg,… juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
