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Advances in Spatio-Temporal Segmentation of Visual Data

Editat de Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko
en Limba Engleză Paperback – 17 ian 2021
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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Specificații

ISBN-13: 9783030354824
ISBN-10: 3030354822
Pagini: 284
Ilustrații: IX, 274 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.44 kg
Ediția:1st ed. 2020
Editura: Springer
Locul publicării:Cham, Switzerland

Cuprins

Adaptive Edge Detection Models and Algorithms.- Swarm Methods of Image Segmentation.- Spatio-temporal Data Interpretation Based on Perceptional Model.- Spatio-Temporal Video Segmentation.

Textul de pe ultima copertă

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. 

Caracteristici

Presents recent research on the spatio-temporal segmentation of visual data Provides systematic information on the research, development, and implementation of advanced spatio-temporal segmentation of visual data for components, networks, and complex systems Addresses software, programmable and hardware components, communications, cloud and IoT-based systems, and IT infrastructures