Deep neural networks trained on simulated Q-meter NMR spectra can extract target polarization with lower fitting uncertainty than conventional least-squares lineshape fitting, at least when the test data come from the same simulator.
Data Augmentation for Deep Learning: A Survey
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Polarized Target Nuclear Magnetic Resonance Measurements with Deep Neural Networks
Deep neural networks trained on simulated Q-meter NMR spectra can extract target polarization with lower fitting uncertainty than conventional least-squares lineshape fitting, at least when the test data come from the same simulator.