Variants of Self-Organizing Maps : Applications in Image Quantization and Compression

Language: English

Published by LAP LAMBERT Academic Publishing, 2009

3838324366 / 9783838324364

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - The self-organizing map (SOM) is an unsupervised learning algorithm which has been successfully applied to various applications. In the last several decades, there have been variants of SOM used in many application domains. In this work, two new SOM algorithms are developed for image quantization and compression. The first algorithm is a sample-size adaptive SOM algorithm that can be used for color quantization of images to adapt to the variations of network parameters and training sample size. Based on the sample-size adaptive self-organizing map, we use the sampling ratio of training data, rather than the conventional weight change between adjacent sweeps, as a stop criterion. As a result, it can significantly speed up the learning process. The second algorithm is a novel classified SOM method for edge preserving quantization of images using an adaptive subcodebook and weighted learning rate. The subcodebook sizes of two classes are automatically adjusted in training iterations that can be estimated incrementally. The proposed weighted learning rate updates the neuron efficiently no matter how large the weighting factor is.…

Seller Inventory # 9783838324364

Title
Variants of Self-Organizing Maps : Applications in Image Quantization and Compression
Author
Chao-Huang Wang
Publisher
LAP LAMBERT Academic Publishing
Publication year
2009
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3838324366
ISBN 13
9783838324364
Item weight
137 grams
Dimensions
220x150x6 mm

AHA-BUCH GmbH

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