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Weight Sharing And Deep Learning For Spectral Data

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IEEE ICASSP 2020 Virtual Conference May 2020

We propose a novel method to co-train deep convolutional neural networks for data sets of differing position specific data. This is an advantage in chemometrics where individual measurements represent exact chemical compounds, e.g. for given wavelengths,

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Weight Sharing And Deep Learning For Spectral Data

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We propose a novel method to co-train deep convolutional neural networks for data sets of differing position specific data. This is an advantage in chemometrics where individual measurements represent exact chemical compounds, e.g. for given wavelengths,