Advances in Spatio-Temporal Segmentation of Visual Data  [electronic resource] / 
edited by Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko. 
 - 1st ed. 2020. 
 - IX, 274 p.  online resource. 
 - Studies in Computational Intelligence,  876  1860-9503 ; .
 - Studies in Computational Intelligence,  876 .
<br/><br/>Adaptive Edge Detection Models and Algorithms -- Swarm Methods of Image Segmentation -- Spatio-temporal Data Interpretation Based on Perceptional Model -- Spatio-Temporal Video Segmentation. 
<br/><br/> 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. . 
<br/><br/><label>ISBN: </label>9783030354800 
<br/><br/><label>Standard No.: </label>10.1007/978-3-030-35480-0  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Engineering mathematics.<br/>Computer vision.<br/>Computational intelligence.<br/>Engineering Mathematics.<br/>Computer Vision.<br/>Computational Intelligence.
<br/><br/><label>LC Class. No.: </label>TA329-348 
<br/><br/><label>Dewey Class. No.: </label>620.00151