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

Advances in spatio-temporal segmenta...

Mashtalir, Vladimir.

Linked to FindBook

Google Book

Amazon

博客來

Advances in spatio-temporal segmentation of visual data

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in spatio-temporal segmentation of visual data/ edited by Vladimir Mashtalir, igor Ruban, Vitaly Levashenko.
other author:	Mashtalir, Vladimir.
Published:	Cham :Springer international Publishing : : 2020.,
Description:	ix, 274 p. :ill., digital ;24 cm.
[NT 15003449]:	Adaptive Edge Detection Models and Algorithms -- Swarm Methods of image Segmentation -- Spatio-temporal Data interpretation Based on Perceptional Model -- Spatio-Temporal Video Segmentation.
Contained By:	Springer eBooks
Subject:	Image segmentation. -
Online resource:	https://doi.org/10.1007/978-3-030-35480-0
ISBN:	9783030354800

Advances in spatio-temporal segmentation of visual data
Advances in spatio-temporal segmentation of visual data[electronic resource] /edited by Vladimir Mashtalir, igor Ruban, Vitaly Levashenko. - Cham :Springer international Publishing :2020. - ix, 274 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8761860-949X ;. - Studies in computational intelligence ;v.876..

Adaptive Edge Detection Models and Algorithms -- Swarm Methods of image Segmentation -- Spatio-temporal Data interpretation Based on Perceptional Model -- Spatio-Temporal Video Segmentation.

This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval. The main focus is on the spatio-temporal segmentation of visual information. Sets of meaningful and manageable image or video parts, defined by visual interest or attention to higher-level semantic issues, are often vital to the efficient and effective processing and interpretation of viewable information. Developing robust methods for spatial and temporal partition represents a key challenge in computer vision and computational intelligence as a whole. This book is intended for students and researchers in the fields of machine learning and artificial intelligence, especially those whose work involves image processing and recognition, video parsing, and content-based image/video retrieval.

ISBN: 9783030354800

Standard No.: 10.1007/978-3-030-35480-0doiSubjects--Topical Terms:

2132796
Image segmentation.

LC Class. No.: TA1638.4 / .A383 2020

Dewey Class. No.: 006.6

Advances in spatio-temporal segmentation of visual data
LDR:02286nmm a2200337 a 4500 001 2215141
003 DE-He213
005 20200518154611.0
006 m d
007 cr nn 008maaau
008 201119s2020 sz s 0 eng d
020 $a 9783030354800 $q (electronic bk.)
020 $a 9783030354794 $q (paper)
024 7 $a 10.1007/978-3-030-35480-0 $2 doi
035 $a 978-3-030-35480-0
040 $a GP $c GP
041 0 $a eng
050 4 $a TA1638.4 $b .A383 2020
072 7 $a TBJ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a TBJ $2 thema
082 0 4 $a 006.6 $2 23
090 $a TA1638.4 $b .A244 2020
245 0 0 $a Advances in spatio-temporal segmentation of visual data $h [electronic resource] / $c edited by Vladimir Mashtalir, igor Ruban, Vitaly Levashenko.
260 $a Cham : $b Springer international Publishing : $b imprint: Springer, $c 2020.
300 $a ix, 274 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.876
505 0 $a Adaptive Edge Detection Models and Algorithms -- Swarm Methods of image Segmentation -- Spatio-temporal Data interpretation Based on Perceptional Model -- Spatio-Temporal Video Segmentation.
520 $a This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval. The main focus is on the spatio-temporal segmentation of visual information. Sets of meaningful and manageable image or video parts, defined by visual interest or attention to higher-level semantic issues, are often vital to the efficient and effective processing and interpretation of viewable information. Developing robust methods for spatial and temporal partition represents a key challenge in computer vision and computational intelligence as a whole. This book is intended for students and researchers in the fields of machine learning and artificial intelligence, especially those whose work involves image processing and recognition, video parsing, and content-based image/video retrieval.
650 0 $a Image segmentation. $3 2132796
650 1 4 $a Engineering Mathematics. $3 3301900
650 2 4 $a image Processing and Computer Vision. $3 3446319
650 2 4 $a Computational intelligence. $3 595739
700 1 $a Mashtalir, Vladimir. $3 3446315
700 1 $a Ruban, igor. $3 3446316
700 1 $a Levashenko, Vitaly. $3 3446317
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in computational intelligence ; $v v.876. $3 3446318
856 4 0 $u https://doi.org/10.1007/978-3-030-35480-0
950 $a Engineering (Springer-11647)