Evolution of spectral data and nonlinear equations

1989 ◽  
Vol 40 (4) ◽  
pp. 459-461 ◽  
Author(s):  
L. A. Sakhnovich
2020 ◽  
Vol 64 (3) ◽  
pp. 30502-1-30502-15
Author(s):  
Kensuke Fukumoto ◽  
Norimichi Tsumura ◽  
Roy Berns

Abstract A method is proposed to estimate the concentration of pigments mixed in a painting, using the encoder‐decoder model of neural networks. The model is trained to output a value that is the same as its input, and its middle output extracts a certain feature as compressed information about the input. In this instance, the input and output are spectral data of a painting. The model is trained with pigment concentration as the middle output. A dataset containing the scattering coefficient and absorption coefficient of each of 19 pigments was used. The Kubelka‐Munk theory was applied to the coefficients to obtain many patterns of synthetic spectral data, which were used for training. The proposed method was tested using spectral images of 33 paintings, which showed that the method estimates, with high accuracy, the concentrations that have a similar spectrum of the target pigments.


1997 ◽  
Author(s):  
Gary Ellrod ◽  
James Nelson, III ◽  
Gary Ellrod ◽  
James Nelson, III
Keyword(s):  

Author(s):  
Yamin Wang ◽  
Gareth Pritchard ◽  
Marc Kimber

Synthetic route for the synthesis of tetrasubstituted furan fatty acids; including experimental details, characterisation, and spectral data of all intermediates.


2019 ◽  
Vol 10 (4) ◽  
pp. 877-886 ◽  
Author(s):  
Chhavi Mangla ◽  
Musheer Ahmad ◽  
Moin Uddin

Sign in / Sign up

Export Citation Format

Share Document