Advances in spatio-temporal segmentation of visual data / Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko, editors.
Mashtalir, Vladimir.; Ruban, Igor.; Levashenko, V. G.
2020
TA1638.4
Available Online

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Title Advances in spatio-temporal segmentation of visual data / Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko, editors.
ISBN 9783030354800 (electronic book)
3030354806 (electronic book)
3030354792
9783030354794
Publication Details Cham : Springer, 2020.
Language English
Description 1 online resource
Call Number TA1638.4
Dewey Decimal Classification 006.6
Summary 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.
Access Note Access limited to authorized users.
Added Author Mashtalir, Vladimir.
Ruban, Igor.
Levashenko, V. G.
Series Studies in computational intelligence ; 876.
Available in Other Form Print version: 9783030354794
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Adaptive Edge Detection Models and Algorithms
Swarm Methods of Image Segmentation
Spatio-temporal Data Interpretation Based on Perceptional Model
Spatio-Temporal Video Segmentation.

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