Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Deep learning-based detection of cat...
~
Liu, Zhigang.
Linked to FindBook
Google Book
Amazon
博客來
Deep learning-based detection of catenary support component defect and fault in high-speed railways
Record Type:
Electronic resources : Monograph/item
Title/Author:
Deep learning-based detection of catenary support component defect and fault in high-speed railways/ by Zhigang Liu, Wenqiang Liu, Junping Zhong.
Author:
Liu, Zhigang.
other author:
Liu, Wenqiang.
Published:
Singapore :Springer Nature Singapore : : 2023.,
Description:
xiii, 239 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:
Overview of Catenary Detection of Electrified Railways -- Advance of Deep Learning -- Catenary Support Components and their Characteristics in High-speed Railways -- Preprocessing of Catenary Support Components' Images -- Positioning of Catenary Support Components -- Detection of Catenary Support Component Defect and Fault -- Detection of The parameters of Catenary Support Devices based on 3D Point Clouds.
Contained By:
Springer Nature eBook
Subject:
High speed trains. -
Online resource:
https://doi.org/10.1007/978-981-99-0953-7
ISBN:
9789819909537
Deep learning-based detection of catenary support component defect and fault in high-speed railways
Liu, Zhigang.
Deep learning-based detection of catenary support component defect and fault in high-speed railways
[electronic resource] /by Zhigang Liu, Wenqiang Liu, Junping Zhong. - Singapore :Springer Nature Singapore :2023. - xiii, 239 p. :ill. (some col.), digital ;24 cm. - Advances in high-speed rail technology,2363-5029. - Advances in high-speed rail technology..
Overview of Catenary Detection of Electrified Railways -- Advance of Deep Learning -- Catenary Support Components and their Characteristics in High-speed Railways -- Preprocessing of Catenary Support Components' Images -- Positioning of Catenary Support Components -- Detection of Catenary Support Component Defect and Fault -- Detection of The parameters of Catenary Support Devices based on 3D Point Clouds.
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.
ISBN: 9789819909537
Standard No.: 10.1007/978-981-99-0953-7doiSubjects--Topical Terms:
2145603
High speed trains.
LC Class. No.: TF1460 / .L58 2023
Dewey Class. No.: 625.1
Deep learning-based detection of catenary support component defect and fault in high-speed railways
LDR
:02906nmm a2200337 a 4500
001
2317511
003
DE-He213
005
20230410154730.0
006
m d
007
cr nn 008maaau
008
230902s2023 si s 0 eng d
020
$a
9789819909537
$q
(electronic bk.)
020
$a
9789819909520
$q
(paper)
024
7
$a
10.1007/978-981-99-0953-7
$2
doi
035
$a
978-981-99-0953-7
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TF1460
$b
.L58 2023
072
7
$a
TRF
$2
bicssc
072
7
$a
TEC009090
$2
bisacsh
072
7
$a
TRF
$2
thema
082
0 4
$a
625.1
$2
23
090
$a
TF1460
$b
.L783 2023
100
1
$a
Liu, Zhigang.
$3
1017493
245
1 0
$a
Deep learning-based detection of catenary support component defect and fault in high-speed railways
$h
[electronic resource] /
$c
by Zhigang Liu, Wenqiang Liu, Junping Zhong.
260
$a
Singapore :
$b
Springer Nature Singapore :
$b
Imprint: Springer,
$c
2023.
300
$a
xiii, 239 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Advances in high-speed rail technology,
$x
2363-5029
505
0
$a
Overview of Catenary Detection of Electrified Railways -- Advance of Deep Learning -- Catenary Support Components and their Characteristics in High-speed Railways -- Preprocessing of Catenary Support Components' Images -- Positioning of Catenary Support Components -- Detection of Catenary Support Component Defect and Fault -- Detection of The parameters of Catenary Support Devices based on 3D Point Clouds.
520
$a
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.
650
0
$a
High speed trains.
$3
2145603
650
0
$a
Fault location (Engineering)
$3
649702
650
0
$a
Deep learning (Machine learning)
$3
3538509
650
1 4
$a
Rail Vehicles.
$3
3598853
650
2 4
$a
Machine Learning.
$3
3382522
650
2 4
$a
Signal, Speech and Image Processing.
$3
3592727
650
2 4
$a
Data Analysis and Big Data.
$3
3538537
650
2 4
$a
Transportation Technology and Traffic Engineering.
$3
2153276
650
2 4
$a
Artificial Intelligence.
$3
769149
700
1
$a
Liu, Wenqiang.
$3
3631665
700
1
$a
Zhong, Junping.
$3
3631666
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
830
0
$a
Advances in high-speed rail technology.
$3
3217762
856
4 0
$u
https://doi.org/10.1007/978-981-99-0953-7
950
$a
Engineering (SpringerNature-11647)
based on 0 review(s)
Location:
ALL
電子資源
Year:
Volume Number:
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
W9453761
電子資源
11.線上閱覽_V
電子書
EB TF1460 .L58 2023
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login