Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30808
Title: Colour-appearance modeling using feedforward networks with Bayesian regularization method. Part I : forward model
Authors: Xin, JH 
Shao, S
Chung, KFL 
Keywords: Back-propagation
Bayesian regularization
Colour-appearance model
Feedforward neural networks
Levenberg-Marquardt algorithm
Issue Date: 2000
Publisher: John Wiley & Sons, Inc.
Source: Color research and application, 2000, v. 25, no. 6, p. 424-434 How to cite?
Journal: Color Research and Application 
Abstract: In this article, a method of predicting colour appearance (from colorimetric attributes to colour-appearance attributes, i.e., forward model) using an artificial neural network is presented. The neural network model developed is a multilayer feedforward neural network model for predicting colour appearance (FNNCAM for short). The model was trained by LUTCHI colour-appearance datasets. The Levenberg-Marquardt algorithm is incorporated into the back-propagation procedure to accelerate the training of FNNCAM and the Bayesian regularization method is applied to the training of neural networks to improve generalization. The results of FNNCAM obtained are quite promising.
URI: http://hdl.handle.net/10397/30808
ISSN: 0361-2317
DOI: 10.1002/1520-6378(200012)25:6<424
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