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MPEG-7 provides a set of descriptors to describe the content of an image. However, how to select or combine descriptors for a specific image classification problem is still an open problem. Currently, descriptors are usually selected by human experts. Moreover, selecting the same set of descriptors for different classes of images may not be reasonable. In this work we propose a MPEG-7 descriptor selection...
In this work, the localized generalization error model (L-GEM) for multilayer perceptron neural network (MLPNN) is derived. The L-GEM is inspired by the fact that a classifier should not be required to recognize unseen samples that are very different from the training samples. Therefore, evaluating a classifier by very different unseen samples may be counter-productive. In the L-GEM, the ldquolocalrdquo...
We had developed the localized generalization error model for supervised learning with minimization of mean square error. In this work, we extend the error model to single layer perceptron neural network (SLPNN). For a trained SLPNN and a given training dataset, the proposed error model bounds above the error for unseen samples which are similar to the training samples. This pilot study is the important...
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