Advances in Spatio-Temporal Segmentation of Visual Data - Couverture rigide

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9783030354794: Advances in Spatio-Temporal Segmentation of Visual Data
Couverture rigide
ISBN 10 : 3030354792 ISBN 13 : 9783030354794
Editeur : Springer Nature Switzerland AG, 2020

Synopsis

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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Éditeur
Springer Nature Switzerland AG
Date d'édition
2020
Langue
anglais
ISBN 10 
3030354792
ISBN 13 
9783030354794
Reliure
Relié
Nombre de pages
283
Éditeur
Mashtalir Vladimir, Ruban Igor, Levashenko Vitaly
Coordonnées du fabricant
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Allemagne

Autres éditions populaires du même titre

9783030354824: Advances in Spatio-Temporal Segmentation of Visual Data

Edition présentée

ISBN 10 :  3030354822 ISBN 13 :  9783030354824
Editeur : Springer, 2021
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