Robust Environmental Perception Reliability by Pan Huihui (18 results)
Robust Environmental Perception and Reliability Co
Pan, Huihui; Wang, Jue; Yu, Xinghu; Sun, Weichao; Gao, Huijun
Language: English
Published by Springer, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
Seller: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Robust Environmental Perception and Reliability Co
Pan, Huihui; Wang, Jue; Yu, Xinghu; Sun, Weichao; Gao, Huijun
Language: English
Published by Springer, 2024
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Softcover
Seller: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Robust Environmental Perception and Reliability Control for Intelligent Vehicles (Recent Advancements in Connected Autonomous Vehicle Technologies, 4)
Pan, Huihui; Wang, Jue; Yu, Xinghu; Sun, Weichao; Gao, Huijun
Language: English
Published by Springer, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Language: English
Published by SPRINGER NATURE, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 299 | Sprache: Englisch | Produktart: Bücher | This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory pred…iction, multi-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes.Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy.Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods.Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers.Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account.Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios. Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.
Language: English
Published by Springer, 2024
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Robust Environmental Perception and Reliability Control for Intelligent Vehicles | Huihui Pan (u. a.) | Taschenbuch | xi | Englisch | 2024 | Springer | EAN 9789819977925 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[do…t]com | Anbieter: preigu.
Robust Environmental Perception and Reliability Control for Intelligent Vehicles: 4 (Recent Advancements in Connected Autonomous Vehicle Technologies)
Pan, Huihui; Wang, Jue; Yu, Xinghu; Sun, Weichao; Gao, Huijun
Language: English
Published by Springer, 2024
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Robust Environmental Perception and Reliability Control for Intelligent Vehicles: 4 (Recent Advancements in Connected Autonomous Vehicle Technologies)
Pan, Huihui; Wang, Jue; Yu, Xinghu; Sun, Weichao; Gao, Huijun
Language: English
Published by Springer, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condition: New. pp. 316 1st ed. 2024 edition NO-PA16APR2015-KAP.
Language: English
Published by Springer, Springer, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi-object tracking…, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes.Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy.Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods.Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers.Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account.Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios.Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.
Language: English
Published by Springer, Springer, 2024
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi-object t…racking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes.Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy.Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods.Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers.Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account.Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios.Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.
Robust Environmental Perception and Reliability Control for Intelligent Vehicles
Pan, Huihui/ Wang, Jue/ Yu, Xinghu/ Sun, Weichao/ Gao, Huijun
Language: English
Published by Springer Nature, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 312 pages. 9.25x6.10x9.21 inches. In Stock.
Language: English
Published by SPRINGER NATURE, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
Seller: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, GermanyBUCHSERVICE / ANTIQUARIAT Lars Lutzer
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Hardcover. Condition: gut. 2023. Robust Environmental Perception and Reliability Control for Intelligent Vehicles In deutscher Sprache. pages.
Language: English
Published by Springer, 2024
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Softcover
- Print on Demand
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
- Print on Demand
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer Nature Singapore, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Captures recent advances of control theory, technological aspects, and applications for intelligent vehiclesProvides a series of latest results in sensors, artificial intelligence, and other fields into intelligent ve…hiclesSummarizes state-.
Language: English
Published by Springer Nature Singapore, Springer Nature Singapore Nov 2024, 2024
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction…, multi-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes.Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy.Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods.Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers.Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account.Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios.Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults. 316 pp. Englisch.
Language: English
Published by Springer Nature Singapore, Springer Nature Singapore Nov 2023, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi…-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes.Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy.Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods.Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers.Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account.Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios.Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults. 316 pp. Englisch.
Language: English
Published by Springer, Springer Nov 2024, 2024
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, mu…lti-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes.Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy.Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods.Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers.Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account.Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios. Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 316 pp. Englisch.
Language: English
Published by Springer, Springer Nov 2023, 2023
Series: Book 4 of 4 - Recent Advancements in Connected Autonomous Vehicle Technologies
- Hardcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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£ 160.53
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi-obj…ect tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes.Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy.Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods.Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers.Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account.Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios. Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 316 pp. Englisch.
