Integrating Statistical Prior Knowledge into Convolutional Neural Networks

Abstract

In this work we show how to integrate prior statistical knowledge, obtained through principal components analysis (PCA), into a convolutional neural network in order to obtain robust predictions even when dealing with corrupted or noisy data. Our network architecture is trained end-to-end and includes a specifically designed layer which incorporates the… (More)
DOI: 10.1007/978-3-319-66182-7_19

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