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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Fast Training of Neural Networks for Image Compression
verfasst von : Yevgeniy Bodyanskiy, Paul Grimm, Sergey Mashtalir, Vladimir Vinarski
Erschienen in: Advances in Data Mining. Applications and Theoretical Aspects
Verlag: Springer Berlin Heidelberg
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The paper considers the problem of image compression by using artificial neural networks (ANN). The main concept of this approach is the reduction of the original feature spaces, what allows us to eliminate the image redundancy and accordingly leads to their compression. Two variants of the neural networks: two layers ANN with the self-learning algorithm based on the weighted informational criterion and auto-associative four-layers feedforward network have been proposed and analyzed.