首页|New Machine Learning Study Findings Reported from Zhejiang University of Technology [Rapid Authentication of Geographical Origins of Baishao (Radix Paeoniae Alba) Slices With Laser-induced Breakdown Spectroscopy Based On ...]
New Machine Learning Study Findings Reported from Zhejiang University of Technology [Rapid Authentication of Geographical Origins of Baishao (Radix Paeoniae Alba) Slices With Laser-induced Breakdown Spectroscopy Based On ...]
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NETL
NSTL
Elsevier
Research findings on Machine Learning are discussed in a new report. According to news originating from Hangzhou, People's Republic of China, by NewsRx correspondents, research stated, "The geographical origin of Baishao (Radix Paeoniae Alba) affects the components and content, which in turn affects its pharmacological action. Laser-induced breakdown spectroscopy (LIBS) was combined with conventional machine learning and deep learning methods to rapidly discriminate the geographical origins of Baishao slices without sample preparation." Funders for this research include National Natural Science Foundation of China (NSFC), Natural Science Foundation of Zhejiang Province. Our news journalists obtained a quote from the research from the Zhejiang University of Technology, "The influence of spatial variation of Baishao slices on the LIBS signal was investigated. The spectra that were averaged using 16-point spectra showed the best origin identification performance, with an accuracy of 96.7% as determined by partial least squares-discriminant analysis (PLS-DA). Meanwhile, the spectra obtained from a single point after voting showed the best origin identification performance using ResNet, with an accuracy of 95.0%."
HangzhouPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningZhejiang University of Technology
NETL
NSTL
Elsevier
