  This paper presents a method to identify substructures in NMR spectra of
mixtures, specifically 2D spectra, using a bespoke image-based Convolutional
Neural Network application. This is done using HSQC and HMBC spectra separately
and in combination. The application can reliably detect substructures in pure
compounds, using a simple network. It can work for mixtures when trained on
pure compounds only. HMBC data and the combination of HMBC and HSQC show better
results than HSQC alone.
