Deep Chemometrics with Data Augmentation
The repository contains two examples of using convolutional neural networks to model spectroscopical data with data augmentation or EMSC as means to handle the variation in baseline.
The approach and background + a comparison with PLS models are further described in https://arxiv.org/pdf/1710.01927 and the blog post https://www.wildcardconsulting.dk/useful-information/deep-chemometrics-deep-learning-for-spectroscopy/
Feel free to leave a comment on the blog post if you find it useful ;-)
Please cite: https://arxiv.org/abs/1710.01927
Commercial support discontinued. Wildcard pharmaceutical consulting: https://www.wildcardconsulting.dk/useful-information/wildcard-pharmaceutical-consulting-will-be-closed/