Advances in Spatio-Temporal Segmentation of Visual Data (1st ed. 2020) (Studies in Computational Intelligence #876)

By: Vladimir Mashtalir and Igor Ruban and Vitaly Levashenko

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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.

Book Quality:: Publisher Quality
ISBN-13:: 9783030354800
Related ISBNs:: 9783030354794
Publisher:: Springer International Publishing
Date of Addition:: 12/21/19
Copyrighted By:: Springer
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Art and Architecture, Computers and Internet, Technology
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: Vladimir Mashtalir
Edited by:: Igor Ruban
Edited by:: Vitaly Levashenko