首页|Researchers from Yili Normal University Report on Findings in MachineLearning ( Combining the fractional order derivative and machine learning for leaf water co ntent estimation of spring wheat using hyper-spectral indices)
Researchers from Yili Normal University Report on Findings in MachineLearning ( Combining the fractional order derivative and machine learning for leaf water co ntent estimation of spring wheat using hyper-spectral indices)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on artificial intelligence are presented in a new report. According to newsreporting out of Yili Normal Un iversity by NewsRx editors, research stated, “Leaf water content (LWC) isa vita l indicator of crop growth and development. While visible and near-infrared (VIS -NIR) spectroscopymakes it possible to estimate crop leaf moisture, spectral pr eprocessing and multiband spectral indiceshave important significance in the qu antitative analysis of LWC.”
Yili Normal UniversityCyborgsEmergin g TechnologiesMachine Learning
NETL
NSTL
