@Article{jihpp.2020.010466,
AUTHOR = {Dongfang Yu, Jinwei Wang},
TITLE = {A Survey on Machine Learning in Chemical Spectral Analysis},
JOURNAL = {Journal of Information Hiding and Privacy Protection},
VOLUME = {2},
YEAR = {2020},
NUMBER = {4},
PAGES = {165--174},
URL = {http://www.techscience.com/jihpp/v2n4/41148},
ISSN = {2637-4226},
ABSTRACT = {Chemical spectral analysis is contemporarily undergoing a revolution 
and drawing much attention of scientists owing to machine learning algorithms, in 
particular convolutional networks. Hence, this paper outlines the major machine 
learning and especially deep learning methods contributed to interpret chemical 
images, and overviews the current application, development and breakthrough in 
different spectral characterization. Brief categorization of reviewed literatures is 
provided for studies per application apparatus: X-Ray spectra, UV-Vis-IR spectra, 
Micro-scope, Raman spectra, Photoluminescence spectrum. End with the 
overview of existing circumstances in this research area, we provide unique insight 
and promising directions for the chemical imaging field to fully couple machine 
learning subsequently.},
DOI = {10.32604/jihpp.2020.010466}
}