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Unervised Learning via Self-Organization - A Dynamic Approach
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Unervised Learning via Self-Organization - A Dynamic Approach
von: Matthew Kyan, Paisarn Muneesawang, Kambiz Jarrah, Ling Guan
Wiley-IEEE Press, 2014
ISBN: 9781118875346
289 Seiten, Download: 7284 KB
 
Format: EPUB, PDF
geeignet für: geeignet für alle DRM-fähigen eReader Apple iPad, Android Tablet PC's Apple iPod touch, iPhone und Android Smartphones Online-Lesen PC, MAC, Laptop

Typ: A (einfacher Zugriff)

 

 
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To aid in intelligent data mining, this book introduces a new family of unsupervised algorithms that have a basis in self-organization, yet are free from many of the constraints typical of other well known self-organizing architectures. It then moves through a series of pertinent real world applications with regards to the processing of multimedia data?from its role in generic image processing techniques such as the automated modeling and removal of impulse noise in digital images, to problems in digital asset management, and its various roles in feature extraction, visual enhancement, segmentation, and analysis of microbiological image data.



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