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Advances in Spatio-Temporal Segmentation of Visual Data / edited by Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko.

Contributor(s): SpringerLink (Online service) | Mashtalir, Vladimir, editor | Ruban, Igor, editor | Levashenko, Vitaly, editor
Material type: materialTypeLabelE-bookSeries: (Studies in Computational Intelligence, 1860-949X; 876).Publisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020.Description: 1 recurso en línea (IX, 274 páginas).ISBN: 9783030354800.Subject: Proceso digital de imágenesOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Adaptive Edge Detection Models and Algorithms -- Swarm Methods of Image Segmentation -- Spatio-temporal Data Interpretation Based on Perceptional Model -- Spatio-Temporal Video Segmentation.
In: Springer eBooksAbstract: 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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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TA1638.4 2020 EB (Browse shelf(Opens below)) Acceso electrónico eBook28022189
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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.

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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