Advances in Spatio-Temporal Segmentation of Visual Data: 876 - Rilegato

Rilegato

ISBN 10: 3030354792 ISBN 13: 9783030354794

Casa editrice: Springer Nature, 2020

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. 

Su questo libro

Dalla quarta di copertina

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. 

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 2020
• Lingua: Inglese
• ISBN 10: 3030354792
• ISBN 13: 9783030354794
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 284
• Redattore: Mashtalir Vladimir, Ruban Igor, Levashenko Vitaly
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3,69115 Heidelberg, Germany; Heidelberg; 69115; Germania