Advances in Spatio-Temporal Segmentation of Visual Data / Studies in Computational Intelligence Bd.876 (PDF)
(Sprache: Englisch)
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...
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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.
Bibliographische Angaben
- 2019, 1st ed. 2020, 274 Seiten, Englisch
- Herausgegeben: Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3030354806
- ISBN-13: 9783030354800
- Erscheinungsdatum: 16.12.2019
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: PDF
- Größe: 9.74 MB
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Sprache:
Englisch
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