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Internal measuring models in trained neural networks for parameter estimation from images

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4 Author(s)
Tian-Jin Feng ; Ocean Univ. of Qingdao, China ; Z. Houkes ; M. J. Korsten ; L. J. Spreeuwers

The internal representations of 'learned' knowledge in neural networks are still poorly understood, even for backpropagation networks. The paper discusses a possible interpretation of learned knowledge of a network trained for parameter estimation from images. The outputs of the hidden layer are the internal components of the output parameters. The input-to-hidden weight maps, functioning as a kind of internal measuring model of the parameter components, include statistical features of the training set and seem to have a clear physical and geometrical meaning

Published in:

Image Processing and its Applications, 1992., International Conference on

Date of Conference:

7-9 Apr 1992