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Found 3 papers, 2 papers with code
Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders
Raman spectroscopy is widely used across scientific domains to characterize the chemical composition of samples in a non-destructive, label-free manner.
Transfer Learning Bayesian Optimization to Design Competitor DNA Molecules for Use in Diagnostic Assays
With the rise in engineered biomolecular devices, there is an increased need for tailor-made biological sequences.
High-throughput molecular imaging via deep learning enabled Raman spectroscopy
Here, we present a comprehensive framework for higher-throughput molecular imaging via deep learning enabled Raman spectroscopy, termed DeepeR, trained on a large dataset of hyperspectral Raman images, with over 1. 5 million spectra (400 hours of acquisition) in total.
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