Name: Cognitive Computing for Smart Automotive Transportation (Chapman & Hall (en Inglés)
SKU: 64396100
Price: 122.99 USD
Availability: InStock
Author: Kanagachidambaresan G. R.,Naganathan Archana,Jayarajan Niresh

portada Cognitive Computing for Smart Automotive Transportation (Chapman & Hall (en Inglés)

Cognitive Computing for Smart Automotive Transportation (Chapman & Hall (en Inglés)

Formato

Libro Físico

Editorial

Crc Pr Inc

Autor

Kanagachidambaresan G. R.,Naganathan Archana,Jayarajan Niresh

Idioma

Inglés

N° páginas

180

Encuadernación

Tapa Dura

ISBN13

9781032487403

Cognitive Computing for Smart Automotive Transportation (Chapman & Hall (en Inglés)

Kanagachidambaresan G. R.,Naganathan Archana,Jayarajan Niresh (Autor) · Crc Pr Inc · Tapa Dura

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Reseña del libro "Cognitive Computing for Smart Automotive Transportation (Chapman & Hall (en Inglés)"

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.