Artificial Neural Networks: applications to Spectroscopy and Pattern Recognition

Currently active keywords for Artificial Neural Networks: applications to Spectroscopy and Pattern Recognition

Machine learning keywords:

ANNs,neural networks,Association rule learning,Deep learning,Back propagation,Multithreaded back propagation,principal component analysis,Wavelet transform,FTIR, multi wavelength linear regression,Quantitative method for spectral based materials,Fourier transform,Reinforcement learning,pattern recognition,Computational learning theory,Decision tree learning,Support vector machines,Bayesian network,Lazy learning,Image Analysis,PCA

Spectroscopy imaging keywords:

machine vision,Full spectral imaging ,multispectral imaging,Chemical imaging,light scattering ,image reconstruction,permittivity,singular value decomposition,spectral plot,scattered 3D,contour3D,histogram,spectral processing,hyper spectral Imaging,spectra,multi-spectral,metamerism, Radiometry,photometry, spectrophotometry,spectral angle mapper,Colorimeter,NIRS,

Disregarded:

electromagnetic wave scattering,raman opticial activity,inferferogram,savitrky golry,blanco method,metamerism