首页|Studies from China Agricultural University in the Area of Machine Learning Descr ibed (Improved Random Patches and Model Transfer for Deriving Leaf Mass Per Area Across Multispecies From Spectral Reflectance)
Studies from China Agricultural University in the Area of Machine Learning Descr ibed (Improved Random Patches and Model Transfer for Deriving Leaf Mass Per Area Across Multispecies From Spectral Reflectance)
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 Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting out of Beijing, People’s Re public of China, by NewsRx editors, research stated, “Leaf mass per area (LMA) s erves as a valuable metric within the field of agriculture, offering valuable in sights into various aspects of leaf structure, including photosynthetic capacity , carbon assimilation, water use efficiency, and overall crop productivity. Mach ine learning, in combination with spectral reflectance analysis, has proven to b e an highly advantageous approach for estimating LMA.” Funders for this research include National Key Technology R&D Progr am, Inner Mongolia Science and technol-ogy project.
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningChina Agricultural Universi ty
NETL
NSTL
