β Scribed by Vladimir Mashtalir, Igor Ruban, Vitaly Levashenko
No coin nor oath required. For personal study only.
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.
Front Matter ....Pages i-ix
Adaptive Edge Detection Models and Algorithms (Kirill Smelyakov, Sergiy Smelyakov, Anastasiya Chupryna)....Pages 1-51
Swarm Methods of Image Segmentation (Igor Ruban, Hennadii Khudov)....Pages 53-99
Spatio-Temporal Data Interpretation Based on Perceptional Model (Anatolii Kargin, Tetyana Petrenko)....Pages 101-159
Spatio-Temporal Video Segmentation (Sergii Mashtalir, Volodymyr Mashtalir)....Pages 161-210
Online Fuzzy Clustering of Data Streams (Yevgeniy Bodyanskiy, Olena Boiko)....Pages 211-241
Fuzzy Systems in Data Mining Tasks (Valentin Filatov, Andriy Kovalenko)....Pages 243-274
Engineering; Engineering Mathematics; Image Processing and Computer Vision; Computational Intelligence
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