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



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Titolo: Advances in Spatio-Temporal Segmentation of Visual Data / / edited by Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Edizione: 1st ed. 2020.
Descrizione fisica: 1 online resource (279 pages)
Disciplina: 621.367
006.6
Soggetto topico: Engineering mathematics
Optical data processing
Computational intelligence
Engineering Mathematics
Image Processing and Computer Vision
Computational Intelligence
Persona (resp. second.): MashtalirVladimir
RubanIgor (Editor of Advances in self-healing systems monitoring and data processing)
LevashenkoVitaly
Nota di contenuto: Adaptive Edge Detection Models and Algorithms -- Swarm Methods of Image Segmentation -- Spatio-temporal Data Interpretation Based on Perceptional Model -- Spatio-Temporal Video Segmentation.
Sommario/riassunto: 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. .
Titolo autorizzato: Advances in Spatio-Temporal Segmentation of Visual Data  Visualizza cluster
ISBN: 3-030-35480-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910366616003321
Lo trovi qui: Univ. Federico II
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Serie: Studies in Computational Intelligence, . 1860-949X ; ; 876