Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Big visual data analysis = scene cla...
~
Chen, Chen.
Big visual data analysis = scene classification and geometric labeling /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Big visual data analysis/ by Chen Chen, Yuzhuo Ren, C.-C. Jay Kuo.
Reminder of title:
scene classification and geometric labeling /
Author:
Chen, Chen.
other author:
Ren, Yuzhuo.
Published:
Singapore :Springer Singapore : : 2016.,
Description:
x, 122 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Computer vision. -
Online resource:
http://dx.doi.org/10.1007/978-981-10-0631-9
ISBN:
9789811006319
Big visual data analysis = scene classification and geometric labeling /
Chen, Chen.
Big visual data analysis
scene classification and geometric labeling /[electronic resource] :by Chen Chen, Yuzhuo Ren, C.-C. Jay Kuo. - Singapore :Springer Singapore :2016. - x, 122 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering,2191-8112. - SpringerBriefs in electrical and computer engineering..
Introduction -- Scene Understanding Datasets -- Indoor/Outdoor classification with Multiple Experts -- Outdoor Scene Classification Using Labeled Segments -- Global-Attributes Assisted Outdoor Scene Geometric Labeling -- Conclusion and Future Work.
This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks.
ISBN: 9789811006319
Standard No.: 10.1007/978-981-10-0631-9doiSubjects--Topical Terms:
561800
Computer vision.
LC Class. No.: TA1634
Dewey Class. No.: 006.37
Big visual data analysis = scene classification and geometric labeling /
LDR
:02226nam a2200349 a 4500
001
862602
003
DE-He213
005
20160823165831.0
006
m d
007
cr nn 008maaau
008
170720s2016 si s 0 eng d
020
$a
9789811006319
$q
(electronic bk.)
020
$a
9789811006296
$q
(paper)
024
7
$a
10.1007/978-981-10-0631-9
$2
doi
035
$a
978-981-10-0631-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TA1634
072
7
$a
TTBM
$2
bicssc
072
7
$a
UYS
$2
bicssc
072
7
$a
TEC008000
$2
bisacsh
072
7
$a
COM073000
$2
bisacsh
082
0 4
$a
006.37
$2
23
090
$a
TA1634
$b
.C518 2016
100
1
$a
Chen, Chen.
$3
1106042
245
1 0
$a
Big visual data analysis
$h
[electronic resource] :
$b
scene classification and geometric labeling /
$c
by Chen Chen, Yuzhuo Ren, C.-C. Jay Kuo.
260
$a
Singapore :
$c
2016.
$b
Springer Singapore :
$b
Imprint: Springer,
300
$a
x, 122 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
SpringerBriefs in electrical and computer engineering,
$x
2191-8112
505
0
$a
Introduction -- Scene Understanding Datasets -- Indoor/Outdoor classification with Multiple Experts -- Outdoor Scene Classification Using Labeled Segments -- Global-Attributes Assisted Outdoor Scene Geometric Labeling -- Conclusion and Future Work.
520
$a
This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks.
650
0
$a
Computer vision.
$3
561800
650
0
$a
Image processing
$x
Digital techniques.
$3
555959
650
1 4
$a
Engineering.
$3
561152
650
2 4
$a
Signal, Image and Speech Processing.
$3
670837
650
2 4
$a
Image Processing and Computer Vision.
$3
670819
650
2 4
$a
Visualization.
$3
574210
700
1
$a
Ren, Yuzhuo.
$3
1106043
700
1
$a
Kuo, C.-C. Jay.
$3
682837
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
SpringerBriefs in electrical and computer engineering.
$3
883975
856
4 0
$u
http://dx.doi.org/10.1007/978-981-10-0631-9
950
$a
Engineering (Springer-11647)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login