首页|Research Conducted at Zhejiang Agriculture & Forestry University Has Updated Our Knowledge about Machine Learning (A Singlewavelength Laser Relaxation Spectroscopy-based Machine Learning Solution for Apple Mechanical Damage Detection)
Research Conducted at Zhejiang Agriculture & Forestry University Has Updated Our Knowledge about Machine Learning (A Singlewavelength Laser Relaxation Spectroscopy-based Machine Learning Solution for Apple Mechanical Damage Detection)
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NETL
NSTL
Springer Nature
Investigators publish new report on Machine Learning. According to news reporting out of Hangzhou, People’s Republic of China, by NewsRx editors, research stated, “Detecting and mitigating mechanical damage in apples during picking and transportation is a critical concern in the agricultural industry. This paper investigates the optimization of a pattern recognition model using single-wavelength laser relaxation spectroscopy for the purpose of apple mechanical damage detection.” Financial supporters for this research include Scientific Research Project of Zhejiang Province, National College Student Research Programme, College Student Research Programme of Zhejiang Province, Zhejiang AF University.
HangzhouPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningSupport Vector MachinesVector MachinesZhejiang Agriculture & Forestry University
NETL
NSTL
Springer Nature
