東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Facial kinship verification = a mach...

Yan, Haibin.

Linked to FindBook

Google Book

Amazon

博客來

Facial kinship verification = a machine learning approach /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Facial kinship verification/ by Haibin Yan, Jiwen Lu.
Reminder of title:	a machine learning approach /
Author:	Yan, Haibin.
other author:	Lu, Jiwen.
Published:	Singapore :Springer Singapore : : 2017.,
Description:	x, 82 p. :ill., digital ;24 cm.
[NT 15003449]:	1. Introduction to Facial Kinship Verification -- 2. Feature Learning for Facial Kinship Verification -- 3. Metric Learning for Facial Kinship Verification -- 4. Video-Based Facial Kinship Verification -- 5. Conclusions and Future Work.
Contained By:	Springer eBooks
Subject:	Biometric identification. -
Online resource:	http://dx.doi.org/10.1007/978-981-10-4484-7
ISBN:	9789811044847

Facial kinship verification = a machine learning approach /
Yan, Haibin.

Facial kinship verificationa machine learning approach /[electronic resource] :by Haibin Yan, Jiwen Lu. - Singapore :Springer Singapore :2017. - x, 82 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - SpringerBriefs in computer science..

1. Introduction to Facial Kinship Verification -- 2. Feature Learning for Facial Kinship Verification -- 3. Metric Learning for Facial Kinship Verification -- 4. Video-Based Facial Kinship Verification -- 5. Conclusions and Future Work.

This book provides the first systematic study of facial kinship verification, a new research topic in biometrics. It presents three key aspects of facial kinship verification: 1) feature learning for kinship verification, 2) metric learning for kinship verification, and 3) video-based kinship verification, and reviews state-of-the-art research findings on facial kinship verification. Many of the feature-learning and metric-learning methods presented in this book can also be easily applied for other face analysis tasks, e.g., face recognition, facial expression recognition, facial age estimation and gender classification. Further, it is a valuable resource for researchers working on other computer vision and pattern recognition topics such as feature-learning-based and metric-learning-based visual analysis.

ISBN: 9789811044847

Standard No.: 10.1007/978-981-10-4484-7doiSubjects--Topical Terms:

729691
Biometric identification.

LC Class. No.: TK7882.B56

Dewey Class. No.: 006.4

Facial kinship verification = a machine learning approach /
LDR:02120nmm a2200349 a 4500 001 2100289
003 DE-He213
005 20170531132155.0
006 m d
007 cr nn 008maaau
008 180119s2017 si s 0 eng d
020 $a 9789811044847 $q (electronic bk.)
020 $a 9789811044830 $q (paper)
024 7 $a 10.1007/978-981-10-4484-7 $2 doi
035 $a 978-981-10-4484-7
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7882.B56
072 7 $a UYT $2 bicssc
072 7 $a UYQV $2 bicssc
072 7 $a COM012000 $2 bisacsh
072 7 $a COM016000 $2 bisacsh
082 0 4 $a 006.4 $2 23
090 $a TK7882.B56 $b Y21 2017
100 1 $a Yan, Haibin. $3 3241817
245 1 0 $a Facial kinship verification $h [electronic resource] : $b a machine learning approach / $c by Haibin Yan, Jiwen Lu.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2017.
300 $a x, 82 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in computer science, $x 2191-5768
505 0 $a 1. Introduction to Facial Kinship Verification -- 2. Feature Learning for Facial Kinship Verification -- 3. Metric Learning for Facial Kinship Verification -- 4. Video-Based Facial Kinship Verification -- 5. Conclusions and Future Work.
520 $a This book provides the first systematic study of facial kinship verification, a new research topic in biometrics. It presents three key aspects of facial kinship verification: 1) feature learning for kinship verification, 2) metric learning for kinship verification, and 3) video-based kinship verification, and reviews state-of-the-art research findings on facial kinship verification. Many of the feature-learning and metric-learning methods presented in this book can also be easily applied for other face analysis tasks, e.g., face recognition, facial expression recognition, facial age estimation and gender classification. Further, it is a valuable resource for researchers working on other computer vision and pattern recognition topics such as feature-learning-based and metric-learning-based visual analysis.
650 0 $a Biometric identification. $3 729691
650 0 $a Face $x Identification. $3 1993453
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Pattern Recognition. $3 891045
650 2 4 $a Biometrics. $3 898232
700 1 $a Lu, Jiwen. $3 3226603
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in computer science. $3 1567571
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-4484-7
950 $a Computer Science (Springer-11645)