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Spectral unmixing of Raman microscopic images of single human cells using Independent Component Analysis
Application of independent component analysis (ICA) as an unmixing and image clustering technique for high spatial resolution Raman maps is reported.
Raman spectral analysis of mixtures with one-dimensional convolutional neural network
Some studies have attempted to extend this technique to the classification of pure compounds in an unknown mixture.
One-dimensional Active Contour Models for Raman Spectrum Baseline Correction
In this paper, a modified version of active contour models in one-dimensional space has been proposed for the baseline correction of Raman spectra.
A Review of 1D Convolutional Neural Networks toward Unknown Substance Identification in Portable Raman Spectrometer
Specifically, we highlight the use of this powerful deep learning technique for handheld Raman spectrometers taking into consideration the potential limit in power consumption and computation ability of handheld systems.
