Language:
English
繁體中文
Help
圖資館首頁
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Deep learning and big data for intel...
~
Ahmed, Khaled R.
Deep learning and big data for intelligent transportationenabling technologies and future trends /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Deep learning and big data for intelligent transportationedited by Khaled R. Ahmed, Aboul Ella Hassanien.
Reminder of title:
enabling technologies and future trends /
other author:
Ahmed, Khaled R.
Published:
Cham :Springer International Publishing :2021.
Description:
x, 264 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Intelligent transportation systems.
Online resource:
https://doi.org/10.1007/978-3-030-65661-4
ISBN:
9783030656614$q(electronic bk.)
Deep learning and big data for intelligent transportationenabling technologies and future trends /
Deep learning and big data for intelligent transportation
enabling 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. 216..
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$q(electronic bk.)
Standard No.: 10.1007/978-3-030-65661-4doiSubjects--Topical Terms:
403795
Intelligent transportation systems.
LC Class. No.: TE228.3 / .D447 2021
Dewey Class. No.: 388.312
Deep learning and big data for intelligent transportationenabling technologies and future trends /
LDR
:03444nmm a2200349 a 4500
001
597882
003
DE-He213
005
20210729134038.0
006
m d
007
cr nn 008maaau
008
211019s2021 sz s 0 eng d
020
$a
9783030656614$q(electronic bk.)
020
$a
9783030656607$q(paper)
024
7
$a
10.1007/978-3-030-65661-4
$2
doi
035
$a
978-3-030-65661-4
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TE228.3
$b
.D447 2021
072
7
$a
UN
$2
bicssc
072
7
$a
COM018000
$2
bisacsh
072
7
$a
UN
$2
thema
072
7
$a
TB
$2
thema
082
0 4
$a
388.312
$2
23
090
$a
TE228.3
$b
.D311 2021
245
0 0
$a
Deep learning and big data for intelligent transportation
$h
[electronic resource] :
$b
enabling technologies and future trends /
$c
edited by Khaled R. Ahmed, Aboul Ella Hassanien.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
x, 264 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Studies in computational intelligence,
$x
1860-949X ;
$v
v.945
505
0
$a
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.
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.
650
0
$a
Intelligent transportation systems.
$3
403795
650
0
$a
Automated vehicles.
$3
849313
650
0
$a
Big data.
$3
609582
650
1 4
$a
Data Engineering.
$3
839346
650
2 4
$a
Transportation Technology and Traffic Engineering.
$3
724870
650
2 4
$a
Computational Intelligence.
$3
338479
700
1
$a
Ahmed, Khaled R.
$3
891372
700
1
$a
Hassanien, Aboul Ella.
$3
266212
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer Nature eBook
830
0
$a
Studies in computational intelligence ;
$v
v. 216.
$3
380871
856
4 0
$u
https://doi.org/10.1007/978-3-030-65661-4
950
$a
Intelligent Technologies and Robotics (SpringerNature-42732)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000196612
電子館藏
1圖書
電子書
EB TE228.3 .D311 2021 2021
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
https://doi.org/10.1007/978-3-030-65661-4
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login