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 Clustering of Visual Information Using Spectral Methods. Eigenvectors and Data Structures
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Clustering of Visual Information Using Spectral Methods. Eigenvectors and Data Structures

автор Uros D. издательство Книга по Требованию Книги
Cтраниц 172        мягкая обложка       
Аннотация:This book can be used to learn basic information about data clustering for readers who want to get familiar with clustering techniques. The proposed algorithm makes no assumption on the number of clusters present in the data set, instead it recursively uncovers clusters in the data until all groups have been found. In addition book shows how specific clustering algorithms can be applied in real world applications, especially in image and video processing. We demonstrated the algorithm on a number of interesting problems in fields of image and video segmentation, shot and scene detection and video summarisation. Applications that use clustering methods for extracting a meaning from data, range from information retrieval, image processing, pattern recognition to biology, economic sciences and many more. Data clustering emerged over the last "digital" years as a powerful tool in data organization and indexing. The main topic of the book is our proposed spectral clustering algorithm which is based on the Markov Random walk interpretation of pair-wise similarities between two data points.
Автор: Uros D.
Издательство: Книга по Требованию
Год:2010
Цена:
2625 руб
Нет в наличии
Поиск: Clustering of Visual Information Using Spectral Methods. Eigenvectors and Data Structures


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