Deep Learning for Autonomous Vehicle Control (Record no. 84687)
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| 000 -LEADER | |
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| fixed length control field | 03822nam a22005895i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-01502-1 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730163518.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220601s2019 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031015021 |
| -- | 978-3-031-01502-1 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 621.3 |
| 100 1# - AUTHOR NAME | |
| Author | Kuutti, Sampo. |
| 245 10 - TITLE STATEMENT | |
| Title | Deep Learning for Autonomous Vehicle Control |
| Sub Title | Algorithms, State-of-the-Art, and Future Prospects / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2019. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XIV, 70 p. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Synthesis Lectures on Advances in Automotive Technology, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | List of Figures -- List of Tables -- Preface -- Introduction -- Deep Learning -- Deep Learning for Vehicle Control -- Safety Validation of Neural Networks -- Concluding Remarks -- Bibliography -- Authors' Biographies. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | The next generation of autonomous vehicles will provide major improvements in traffic flow, fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of autonomous vehicles, one aspect of which is robust and adaptable vehicle control. Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which it may encounter after deployment. However, deep learning methods have shown great promise in not only providing excellent performance for complex and non-linear control problems, but also in generalizing previously learned rules to new scenarios. For these reasons, the use of deep neural networks for vehicle control has gained significant interest. In this book, we introduce relevant deep learning techniques, discuss recent algorithms applied to autonomous vehicle control, identify strengths and limitations of available methods, discuss research challenges in the field, and provide insights into the future trends in this rapidly evolving field. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Fallah, Saber. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Bowden, Richard. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Barber, Phil. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-01502-1 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2019. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
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| -- | computer |
| -- | c |
| -- | rdamedia |
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| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Electrical engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Mechanical engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Automotive engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Transportation engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Traffic engineering. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Electrical and Electronic Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Mechanical Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Automotive Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Transportation Technology and Traffic Engineering. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2576-8131 |
| 912 ## - | |
| -- | ZDB-2-SXSC |
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