Image classification using neural networks

user-5ef9583f4c775ed682ecca0f(2019)

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摘要
[en] A computer-implemented method for training a neural network for classifying image data and a related computer program product are disclosed. A labelled input data set comprising a plurality of labelled image data samples is provided together with a neural network. The neural network comprises an input layer, at least one intermediate layer, and an output layer having one channel per label class. Each channel provides a mapping of labelled image data samples onto feature vectors. Furthermore, the input layer of a decoder network for reconstructing image data samples at its output is connecting the output layer of the neural network. A classifier predicts class labels as the labels of those channels for which a normed distance of its feature vector relative to a pre-determined reference point is smallest. A loss function for the neural network is suitable for steering, for each channel, the feature vectors onto which image data samples of the associated class are mapped, into a convex target region around the pre-determined reference point.
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