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Titlebook: Advances in Spatio-Temporal Segmentation of Visual Data; Vladimir Mashtalir,Igor Ruban,Vitaly Levashenko Book 2020 Springer Nature Switzer

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发表于 2025-3-21 16:05:57 | 显示全部楼层 |阅读模式
期刊全称Advances in Spatio-Temporal Segmentation of Visual Data
影响因子2023Vladimir Mashtalir,Igor Ruban,Vitaly Levashenko
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发行地址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
学科分类Studies in Computational Intelligence
图书封面Titlebook: Advances in Spatio-Temporal Segmentation of Visual Data;  Vladimir Mashtalir,Igor Ruban,Vitaly Levashenko Book 2020 Springer Nature Switzer
影响因子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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发表于 2025-3-21 21:47:05 | 显示全部楼层
Advances in Spatio-Temporal Segmentation of Visual Data
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Swarm Methods of Image Segmentation,hods. Currently, methods of searching for global extremum are being developed, which provide the convergence to the exact solution of the optimization problem, provide the optimal (minimum or maximum) value of the objective function. Such methods include meta-heuristic optimization methods, which, u
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1860-949X fields of machine learning and artificial intelligence, especially those whose work involves image processing and recognition, video parsing, and content-based image/video retrieval. .978-3-030-35482-4978-3-030-35480-0Series ISSN 1860-949X Series E-ISSN 1860-9503
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Swarm Methods of Image Segmentation,ltidimensional space of alternatives. Searching for rational solutions in a multidimensional space of alternative is peculiarized by non-linearity, non-differentiation, multi-extremality, ravine surface, lack of the analytic expression of objective functions, high computational complexity, high dime
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Spatio-Temporal Video Segmentation,ctured data. In such a way, one of the promising ways is spatial-temporal segmentation as frame partitions represent certain spatial image content. Also, properties were formulated and proved which ultimately determine the characteristics of permissible segmentation transformations when searching fo
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