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A novel machine learning scheme for classification of medicinal herbs based on 2D-FTIR fingerprints.

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Bibliographic Details
Title: A novel machine learning scheme for classification of medicinal herbs based on 2D-FTIR fingerprints.
Authors: Yoon TL; School of Physics, Universiti Sains Malaysia, 11800 Penang, Malaysia. Electronic address: tlyoon@usm.my., Yeap ZQ; School of Physics, Universiti Sains Malaysia, 11800 Penang, Malaysia; School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Penang, Malaysia., Tan CS; Material Characterization Team, PerkinElmer, Inc. Petaling Jaya, Malaysia., Chen Y; School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China., Chen J; Research Center for Medicinal Plant, Institute of Agricultural Bio-resource, Fujian Academy of Agricultural Sciences, Fuzhou 350003, Fujian, China., Yam MF; School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Penang, Malaysia; College of Pharmacy, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, Fujian, China. Electronic address: yammunfei@usm.my.
Source: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy [Spectrochim Acta A Mol Biomol Spectrosc] 2022 Feb 05; Vol. 266, pp. 120440. Date of Electronic Publication: 2021 Sep 27.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: England NLM ID: 9602533 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-3557 (Electronic) Linking ISSN: 13861425 NLM ISO Abbreviation: Spectrochim Acta A Mol Biomol Spectrosc Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1873-3557
DOI:10.1016/j.saa.2021.120440