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Optical Data Analysis: Decoding Optical Data with Machine Learning (Laser Photonics Rev. 15(2)/2021)
Author(s) -
Fang Jie,
Swain Anand,
Unni Rohit,
Zheng Yuebing
Publication year - 2021
Publication title -
laser and photonics reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.778
H-Index - 116
eISSN - 1863-8899
pISSN - 1863-8880
DOI - 10.1002/lpor.202170017
Subject(s) - decoding methods , photonics , 3d optical data storage , optical physics , computer science , focus (optics) , laser , data acquisition , data analysis , artificial intelligence , optics , physics , telecommunications , data mining , plasma , quantum mechanics , operating system
In article number 2000422, Yuebing Zheng and co‐workers review the advances of machine learning (ML) in decoding complex optical data, enabling rapid and accurate analysis of optical spectra and images. ML‐assisted optical data decoding can shorten the data analysis time by skipping the intermediate segments and provide an insight into the unknown physics. Recent progress has been discussed with a focus on applications in disease diagnosis, noninvasive biological study, information technology, fundamental studies in optics, and materials science and engineering.