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{ "item_title" : "Advances in Spatio-Temporal Segmentation of Visual Data", "item_author" : [" Vladimir Mashtalir", "Igor Ruban", "Vitaly Levashenko "], "item_description" : "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. ", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/03/035/479/3030354792_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Advances in Spatio-Temporal Segmentation of Visual Data|Vladimir Mashtalir

Advances in Spatio-Temporal Segmentation of Visual Data

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Overview

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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Details

  • ISBN-13: 9783030354794
  • ISBN-10: 3030354792
  • Publisher: Springer
  • Publish Date: January 2020
  • Dimensions: 9.21 x 6.14 x 0.69 inches
  • Shipping Weight: 1.27 pounds
  • Page Count: 274

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