Xiaohui wu (41 Ergebnisse)

Paperback. Zustand: New.

Paperback. Zustand: New.

Zustand: New. 2025. paperback. . . . . . Books ship from the US and Ireland.

Taschenbuch. Zustand: Neu. Neuware - For over a thousand years, the murals of the Mogao Grottoes in Dunhuang have stood as one of China' s greatest artistic treasures--an extraordinary fusion of spiritual devotion, imagination, and craftsmanship.Inspired by these sacred artworks, this book presents 24 carefully selected motifs, transforming ancient wall paintings into a creative, hands-on experience. From symbolic lotus flowers and pomegranates to celestial beings and intricate patterns, each coloring project invites you to reconnect with tradition through the mindful act of coloring.Printed on high-quality paper and designed for all skill levels, these line drawings offer a peaceful journey into art, culture, and self-expression. Whether for relaxation or exploration, this book opens a doorway to the timeless beauty and wisdom of Dunhuang.Now, bring ancient images to life, explore hidden meanings, and develop a sensitivity to color and detail.…

Paperback. Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: New.

Paperback. Zustand: New. Video Based Machine Learning for Traffic Intersections describes the development of computer vision and machine learning-based applications for Intelligent Transportation Systems (ITS) and the challenges encountered during their deployment. This book presents several novel approaches, including a two-stream convolutional network architecture for vehicle detection, tracking, and near-miss detection; an unsupervised approach to detect near-misses in fisheye intersection videos using a deep learning model combined with a camera calibration and spline-based mapping method; and algorithms that utilize video analysis and signal timing data to accurately detect and categorize events based on the phase and type of conflict in pedestrian-vehicle and vehicle-vehicle interactions.The book makes use of a real-time trajectory prediction approach, combined with aligned Google Maps information, to estimate vehicle travel time across multiple intersections. Novel visualization software, designed by the authors to serve traffic practitioners, is used to analyze the efficiency and safety of intersections. The software offers two modes: a streaming mode and a historical mode, both of which are useful to traffic engineers who need to quickly analyze trajectories to better understand traffic behavior at an intersection.Overall, this book presents a comprehensive overview of the application of computer vision and machine learning to solve transportation-related problems. Video Based Machine Learning for Traffic Intersections demonstrates how these techniques can be used to improve safety, efficiency, and traffic flow, as well as identify potential conflicts and issues before they occur. The range of novel approaches and techniques presented offers a glimpse of the exciting possibilities that lie ahead for ITS research and development.Key Features:Describes the development and challenges associated with Intelligent Transportation Systems (ITS)Provides novel visualization software designed to serve traffic practitioners in analyzing the efficiency and safety of an intersectionHas the potential to proactively identify potential conflict situations and develop an early warning system for real-time vehicle-vehicle and pedestrian-vehicle conflicts.…

Zustand: New.

Paperback. Zustand: Brand New. 194 pages. 9.18x6.12x9.21 inches. In Stock.

Hardcover. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Zustand: New.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: New. Video Based Machine Learning for Traffic Intersections describes the development of computer vision and machine learning-based applications for Intelligent Transportation Systems (ITS) and the challenges encountered during their deployment. This book presents several novel approaches, including a two-stream convolutional network architecture for vehicle detection, tracking, and near-miss detection; an unsupervised approach to detect near-misses in fisheye intersection videos using a deep learning model combined with a camera calibration and spline-based mapping method; and algorithms that utilize video analysis and signal timing data to accurately detect and categorize events based on the phase and type of conflict in pedestrian-vehicle and vehicle-vehicle interactions.The book makes use of a real-time trajectory prediction approach, combined with aligned Google Maps information, to estimate vehicle travel time across multiple intersections. Novel visualization software, designed by the authors to serve traffic practitioners, is used to analyze the efficiency and safety of intersections. The software offers two modes: a streaming mode and a historical mode, both of which are useful to traffic engineers who need to quickly analyze trajectories to better understand traffic behavior at an intersection.Overall, this book presents a comprehensive overview of the application of computer vision and machine learning to solve transportation-related problems. Video Based Machine Learning for Traffic Intersections demonstrates how these techniques can be used to improve safety, efficiency, and traffic flow, as well as identify potential conflicts and issues before they occur. The range of novel approaches and techniques presented offers a glimpse of the exciting possibilities that lie ahead for ITS research and development.Key Features:Describes the development and challenges associated with Intelligent Transportation Systems (ITS)Provides novel visualization software designed to serve traffic practitioners in analyzing the efficiency and safety of an intersectionHas the potential to proactively identify potential conflict situations and develop an early warning system for real-time vehicle-vehicle and pedestrian-vehicle conflicts.…

Hardcover. Zustand: Brand New. 208 pages. 9.19x6.13x0.63 inches. In Stock.

Zustand: New.

Zustand: New.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Taschenbuch. Zustand: Neu. The Proceedings of 2023 International Conference on Wireless Power Transfer (ICWPT2023) | Volume I | Chunwei Cai (u. a.) | Taschenbuch | Lecture Notes in Electrical Engineering | xi | Englisch | 2025 | Springer | EAN 9789819708758 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. The Proceedings of 2023 International Conference on Wireless Power Transfer (ICWPT2023) | Volume III | Chunwei Cai (u. a.) | Taschenbuch | Lecture Notes in Electrical Engineering | xii | Englisch | 2025 | Springer | EAN 9789819708673 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. The Proceedings of 2023 International Conference on Wireless Power Transfer (ICWPT2023) | Volume IV | Chunwei Cai (u. a.) | Taschenbuch | Lecture Notes in Electrical Engineering | xii | Englisch | 2025 | Springer | EAN 9789819708710 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. The Proceedings of 2023 International Conference on Wireless Power Transfer (ICWPT2023) | Volume II | Chunwei Cai (u. a.) | Taschenbuch | Lecture Notes in Electrical Engineering | xii | Englisch | 2025 | Springer | EAN 9789819708796 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …