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Advances in spatio-temporal segmenta...
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Levashenko, Vitaly.
Advances in spatio-temporal segmentation of visual data
Record Type:
Electronic resources : Monograph/item
Title/Author:
Advances in spatio-temporal segmentation of visual dataedited 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.
Contained By:
Springer eBooks
Subject:
Image segmentation.
Online resource:
https://doi.org/10.1007/978-3-030-35480-0
ISBN:
9783030354800$q(electronic bk.)
Advances in spatio-temporal segmentation of visual data
Advances in spatio-temporal segmentation of visual data
[electronic resource] /edited by Vladimir Mashtalir, igor Ruban, Vitaly Levashenko. - Cham :Springer international Publishing :2020. - ix, 274 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8761860-949X ;. - Studies in computational intelligence ;v. 216..
Adaptive Edge Detection Models and Algorithms -- Swarm Methods of image Segmentation -- Spatio-temporal Data interpretation Based on Perceptional Model -- Spatio-Temporal Video Segmentation.
This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval. The main focus is on the spatio-temporal segmentation of visual information. Sets of meaningful and manageable image or video parts, defined by visual interest or attention to higher-level semantic issues, are often vital to the efficient and effective processing and interpretation of viewable information. Developing robust methods for spatial and temporal partition represents a key challenge in computer vision and computational intelligence as a whole. This book is intended for students and researchers in the fields of machine learning and artificial intelligence, especially those whose work involves image processing and recognition, video parsing, and content-based image/video retrieval.
ISBN: 9783030354800$q(electronic bk.)
Standard No.: 10.1007/978-3-030-35480-0doiSubjects--Topical Terms:
710586
Image segmentation.
LC Class. No.: TA1638.4 / .A383 2020
Dewey Class. No.: 006.6
Advances in spatio-temporal segmentation of visual data
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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.
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EB TA1638.4 .A244 2020 2020
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