Advances in Spatio-Temporal Segmentation of Visual Data (Studies in Computational Intelligence, 876)
Language: English
Published by Springer, 2020
Series: Book 379 of 538 - Studies in Computational Intelligence
- Hardcover
- New

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- Title
- Advances in Spatio-Temporal Segmentation of Visual Data (Studies in Computational Intelligence, 876)
- Publisher
- Springer
- Publication year
- 2020
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3030354792
- ISBN 13
- 9783030354794
- Series
- Book 379 of 538: Studies in Computational Intelligence
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
Biblios
frankfurt am main, hessen, Germany
4-star seller
AbeBooks seller since September 10, 2024
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