Overview
- 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
Part of the book series: Studies in Computational Intelligence (SCI, volume 876)
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Table of contents (6 chapters)
Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Advances in Spatio-Temporal Segmentation of Visual Data
Editors: Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-35480-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-35479-4Published: 16 January 2020
Softcover ISBN: 978-3-030-35482-4Published: 17 January 2021
eBook ISBN: 978-3-030-35480-0Published: 16 December 2019
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: IX, 274
Topics: Engineering Mathematics, Image Processing and Computer Vision, Computational Intelligence