Cognitive Computing Smart Automotive (17 results)

hardcover. Condition: Very Good.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New. G. R. Kanagachidambaresan is a professor in the Department of Computer Science and Engineering at Vel Tech Rangarajan Dr. Sagunthala R&ampD Institute of Science and Technology. He earned his PhD from Anna University in 2017. Presently, .

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Hardback. Condition: New. New copy - Usually dispatched within 4 working days.

Condition: New. In English.

Hardback. Condition: New. This reference book explores the integration of cognitive computing technologies in the automotive industry to enhance smart transportation systems. It focuses on how AI, machine learning, and data analytics can improve vehicle automation, safety, and efficiency. Automation can support driverless vehicle transportation and bridge the gap between manual control and fully automated navigation systems. The text introduces a discussion on numerous applications of cognitive computing in smart transportation, motion planning, situation awareness, dynamic driving, adaptive behavior, human intent measurement, and predictive analysis.Key Features. Discusses basic concepts and architecture of cognitive computing for vehicular systems. Presents technologies to measure human intent for vehicle safety, including emergency management systems (EMS). Covers the perception and localization processes in autonomous driving through LiDAR, GPS, and Stereo vision data with critical decision-making and simulation results. Elucidates the application of motion planning for smart transportation. Covers visual perception technologies for advanced driver assistance systems (ADAS) through deep learning.The text is primarily written for graduate students, academic researchers, and professionals in the fields of computer science, electrical engineering, automotive engineering, and civil engineering.…

Hardcover. Condition: Brand New. 192 pages. 9.18x6.12x9.45 inches. In Stock.

Hardback. Condition: New. This reference book explores the integration of cognitive computing technologies in the automotive industry to enhance smart transportation systems. It focuses on how AI, machine learning, and data analytics can improve vehicle automation, safety, and efficiency. Automation can support driverless vehicle transportation and bridge the gap between manual control and fully automated navigation systems. The text introduces a discussion on numerous applications of cognitive computing in smart transportation, motion planning, situation awareness, dynamic driving, adaptive behavior, human intent measurement, and predictive analysis.Key Features. Discusses basic concepts and architecture of cognitive computing for vehicular systems. Presents technologies to measure human intent for vehicle safety, including emergency management systems (EMS). Covers the perception and localization processes in autonomous driving through LiDAR, GPS, and Stereo vision data with critical decision-making and simulation results. Elucidates the application of motion planning for smart transportation. Covers visual perception technologies for advanced driver assistance systems (ADAS) through deep learning.The text is primarily written for graduate students, academic researchers, and professionals in the fields of computer science, electrical engineering, automotive engineering, and civil engineering.…

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This reference book explores the integration of cognitive computing technologies in the automotive industry to enhance smart transportation systems. It focuses on how AI, machine learning, and data analytics can improve vehicle automation, safety, and efficiency. Automation can support driverless vehicle transportation and bridge the gap between manual control and fully automated navigation systems. The text introduces a discussion on numerous applications of cognitive computing in smart transportation, motion planning, situation awareness, dynamic driving, adaptive behavior, human intent measurement, and predictive analysis.Key Features:- Discusses basic concepts and architecture of cognitive computing for vehicular systems.- Presents technologies to measure human intent for vehicle safety, including emergency management systems (EMS).- Covers the perception and localization processes in autonomous driving through LiDAR, GPS, and Stereo vision data with critical decision making and simulation results.- Elucidates the application of motion planning for smart transportation.- Covers visual perception technologies for advanced driver assistance systems (ADAS) through deep learning.The text is primarily written for graduate students, academic researchers, and professionals in the fields of computer science, electrical engineering, automotive engineering, and civil engineering. 182 pp. Englisch.…

Hardcover. Condition: new. Hardcover. This reference book explores the integration of cognitive computing technologies in the automotive industry to enhance smart transportation systems. It focuses on how AI, machine learning, and data analytics can improve vehicle automation, safety, and efficiency. Automation can support driverless vehicle transportation and bridge the gap between manual control and fully automated navigation systems. The text introduces a discussion on numerous applications of cognitive computing in smart transportation, motion planning, situation awareness, dynamic driving, adaptive behavior, human intent measurement, and predictive analysis.Key Features: Discusses basic concepts and architecture of cognitive computing for vehicular systems. Presents technologies to measure human intent for vehicle safety, including emergency management systems (EMS). Covers the perception and localization processes in autonomous driving through LiDAR, GPS, and Stereo vision data with critical decisionmaking and simulation results. Elucidates the application of motion planning for smart transportation. Covers visual perception technologies for advanced driver assistance systems (ADAS) through deep learning.The text is primarily written for graduate students, academic researchers, and professionals in the fields of computer science, electrical engineering, automotive engineering, and civil engineering. The reference book explores the integration of cognitive computing technologies in the automotive industry to enhance smart transportation systems. It focuses on how AI, machine learning, and data analytics can improve vehicle automation, safety, and efficiency. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This reference book explores the integration of cognitive computing technologies in the automotive industry to enhance smart transportation systems. It focuses on how AI, machine learning, and data analytics can improve vehicle automation, safety, and efficiency. Automation can support driverless vehicle transportation and bridge the gap between manual control and fully automated navigation systems. The text introduces a discussion on numerous applications of cognitive computing in smart transportation, motion planning, situation awareness, dynamic driving, adaptive behavior, human intent measurement, and predictive analysis.Key Features:- Discusses basic concepts and architecture of cognitive computing for vehicular systems.- Presents technologies to measure human intent for vehicle safety, including emergency management systems (EMS).- Covers the perception and localization processes in autonomous driving through LiDAR, GPS, and Stereo vision data with critical decision making and simulation results.- Elucidates the application of motion planning for smart transportation.- Covers visual perception technologies for advanced driver assistance systems (ADAS) through deep learning.The text is primarily written for graduate students, academic researchers, and professionals in the fields of computer science, electrical engineering, automotive engineering, and civil engineering.…