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Deep learning and big data for intel...

Ahmed, Khaled R.

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Deep learning and big data for intelligent transportation = enabling technologies and future trends /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deep learning and big data for intelligent transportation/ edited by Khaled R. Ahmed, Aboul Ella Hassanien.
其他題名:	enabling technologies and future trends /
其他作者:	Ahmed, Khaled R.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	x, 264 p. :ill. (some col.), digital ;24 cm.
內容註:	Part I: Big Data and Autonomous Vehicles -- Big Data Technologies with Computanational Model Computing using HADOOP with Scheduling Challeges -- Big Data for Autonomous Vehicles -- Part II: Deep Learning &Object detection for Safe driving -- Analysis of Target Detection and Tracking for Intelligent Vision System -- Enhanced end-to-end system for autonomous driving using deep convolutional networks -- Deep Learning Technologies to mitigate Deer-Vehicle Collisions -- Night-to-Day Road Scene Translation Using Generative Adversarial Network with Structural Similarity Loss for Night Driving Safety -- Safer-Driving: Application of Deep Transfer Learning to Build Intelligent Transportation Systems -- Leveraging CNN Deep Learning Model for Smart Parking -- Estimating Crowd Size for Public Place Surveillance using Deep Learning -- Part III: AI & IoT for intelligent transportation -- IoT Based Regional Speed Restriction Using Smart Sign Boards -- Synergy of Internet of Things with Cloud, Artificial Intelligence and Blockchain for Empowering Autonomous Vehicles -- Combining Artificial Intelligence with Robotic Process Automation - An Intelligent Automation Approach.
Contained By:	Springer Nature eBook
標題:	Intelligent transportation systems. -
電子資源:	https://doi.org/10.1007/978-3-030-65661-4
ISBN:	9783030656614

Deep learning and big data for intelligent transportation = enabling technologies and future trends /
Deep learning and big data for intelligent transportationenabling technologies and future trends /[electronic resource] :edited by Khaled R. Ahmed, Aboul Ella Hassanien. - Cham :Springer International Publishing :2021. - x, 264 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.9451860-949X ;. - Studies in computational intelligence ;v.945..

Part I: Big Data and Autonomous Vehicles -- Big Data Technologies with Computanational Model Computing using HADOOP with Scheduling Challeges -- Big Data for Autonomous Vehicles -- Part II: Deep Learning &Object detection for Safe driving -- Analysis of Target Detection and Tracking for Intelligent Vision System -- Enhanced end-to-end system for autonomous driving using deep convolutional networks -- Deep Learning Technologies to mitigate Deer-Vehicle Collisions -- Night-to-Day Road Scene Translation Using Generative Adversarial Network with Structural Similarity Loss for Night Driving Safety -- Safer-Driving: Application of Deep Transfer Learning to Build Intelligent Transportation Systems -- Leveraging CNN Deep Learning Model for Smart Parking -- Estimating Crowd Size for Public Place Surveillance using Deep Learning -- Part III: AI & IoT for intelligent transportation -- IoT Based Regional Speed Restriction Using Smart Sign Boards -- Synergy of Internet of Things with Cloud, Artificial Intelligence and Blockchain for Empowering Autonomous Vehicles -- Combining Artificial Intelligence with Robotic Process Automation - An Intelligent Automation Approach.

This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today's technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle's speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies.

ISBN: 9783030656614

Standard No.: 10.1007/978-3-030-65661-4doiSubjects--Topical Terms:

1066364
Intelligent transportation systems.

LC Class. No.: TE228.3 / .D447 2021

Dewey Class. No.: 388.312

Deep learning and big data for intelligent transportation = enabling technologies and future trends /
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520 $a This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today's technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle's speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies.
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