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200117 ||| eng |
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|a 9783030354800
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| 100 |
1 |
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|a Mashtalir, Vladimir
|e [editor]
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| 245 |
0 |
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|a Advances in Spatio-Temporal Segmentation of Visual Data
|h Elektronische Ressource
|c edited by Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko
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| 250 |
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|a 1st ed. 2020
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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| 300 |
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|a IX, 274 p
|b online resource
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| 505 |
0 |
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|a 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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| 653 |
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|a Engineering mathematics
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| 653 |
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|a Computer vision
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| 653 |
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|a Computational intelligence
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| 653 |
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|a Computer Vision
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| 653 |
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|a Computational Intelligence
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| 653 |
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|a Engineering Mathematics
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| 700 |
1 |
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|a Ruban, Igor
|e [editor]
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| 700 |
1 |
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|a Levashenko, Vitaly
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Studies in Computational Intelligence
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| 028 |
5 |
0 |
|a 10.1007/978-3-030-35480-0
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-030-35480-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 620.00151
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| 520 |
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|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.
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