| 期刊全稱(chēng) | Advances in Spatio-Temporal Segmentation of Visual Data | | 影響因子2023 | Vladimir Mashtalir,Igor Ruban,Vitaly Levashenko | | 視頻video | http://file.papertrans.cn/150/149848/149848.mp4 | | 發(fā)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 | | 學(xué)科分類(lèi) | Studies in Computational Intelligence | | 圖書(shū)封面 |  | | 影響因子 | 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.?. | | Pindex | Book 2020 |
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