9789819909551 - deep learning-based detection of catenary support component defect and fault in high-speed railways (advances in high-speed rail technology) von liu, zhigang; liu, wenqiang; zhong, junping (3 Ergebnisse)

- Softcover
Anbieter: Buchpark, Trebbin, , DeutschlandBuchpark
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht
EUR 91,34
EUR 105,00 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book focuses on the deep learning technologies and their applications in the catenary detection of high-speed railways. As the only source of power for high-speed trains, the catenary's service performance directly affects the safe opera…tion of high-speed railways. This book systematically shows the latest research results of catenary detection in high-speed railways, especially the detection of catenary support component defect and fault. Some methods or algorithms have been adopted in practical engineering. These methods or algorithms provide important references and help the researcher, scholar, and engineer on pantograph and catenary technology in high-speed railways. Unlike traditional detection methods of catenary support component based on image processing, some advanced methods in the deep learning field, including convolutional neural network, reinforcement learning, generative adversarial network, etc., are adopted and improved in this book. The main contents include the overview of catenary detection of electrified railways, the introduction of some advance of deep learning theories, catenary support components and their characteristics in high-speed railways, the image reprocessing of catenary support components, the positioning of catenary support components, the detection of defect and fault, the detection based on 3D point cloud, etc.

- Softcover
Anbieter: preigu, Osnabrück, Deutschlandpreigu
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 149,00
EUR 70,00 VersandVersand von Deutschland nach USAAnzahl: 5 verfügbar
Taschenbuch. Zustand: Neu. Deep Learning-Based Detection of Catenary Support Component Defect and Fault in High-Speed Railways | Zhigang Liu (u. a.) | Taschenbuch | xiii | Englisch | 2024 | Springer | EAN 9789819909551 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]har…tmann[at]springer[dot]com | Anbieter: preigu.

- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 175,77
EUR 62,20 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on the deep learning technologies and their applications in the catenary detection of high-speed railways. As the only source of power for high-speed trains, the catenary's service performance directly affects the safe operation of…high-speed railways. This book systematically shows the latest research results of catenary detection in high-speed railways, especially the detection of catenary support component defect and fault. Some methods or algorithms have been adopted in practical engineering. These methods or algorithms provide important references and help the researcher, scholar, and engineer on pantograph and catenary technology in high-speed railways. Unlike traditional detection methods of catenary support component based on image processing, some advanced methods in the deep learning field, including convolutional neural network, reinforcement learning, generative adversarial network, etc., are adopted and improved in this book. The main contents include the overview of catenary detection of electrified railways, the introduction of some advance of deep learning theories, catenary support components and their characteristics in high-speed railways, the image reprocessing of catenary support components, the positioning of catenary support components, the detection of defect and fault, the detection based on 3D point cloud, etc.